system

Abstract

We provide the system. [Solution] A system including a means for inputting the user's experience and future goals, a means for recommending suitable individuals within the group company based on the relevant information, and a means for automatically setting up appointments with the recommended individuals.

Description

Technical Field

[0001] The technology of the present disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] [[ID=�4]] In conventional systems, it has been difficult for employees to share their experiences and future goals and find appropriate people based on them. Also, it takes time to set appointments with the found people.

Means for Solving the Problems

[0005] The present invention provides a means for inputting the user's experience and future goals, a person recommendation means for recommending appropriate individuals within the group company based on the relevant information, and an appointment setting means for automatically setting appointments with the recommended individuals. In particular, the person recommendation means learns the characteristics of individuals from the employee's output and registers them in a database. The appointment setting means sets appointments such as 1-on-1 meetings according to the user's wishes. This makes it possible for employees to efficiently share their experience and future goals, find appropriate individuals, and set appointments. [Brief explanation of the drawing]

[0006] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Embodiment 1 of Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1 of Form Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2 of Embodiment 2. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2 of Form Example 2. [Figure 15] This is a sequence diagram showing the processing flow of the data processing system in Embodiment 3 of Example 3. [Figure 16] This is a sequence diagram showing the processing flow of the data processing system in Application Example 3 of Form Example 3. [Figure 17] This is a sequence diagram showing the processing flow of the data processing system in Example 1 of the Form 1 when an emotion engine is combined. [Figure 18] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] This is a sequence diagram showing the processing flow of the data processing system in Example 2 of the Form 2 when an emotion engine is combined. [Figure 20] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] This is a sequence diagram showing the processing flow of the data processing system in Example 3 of the Form 3 when an emotion engine is combined. [Figure 22] This is a sequence diagram showing the processing flow of the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. [Figure 23] This is a sequence diagram showing the processing flow of a data processing system in another embodiment. [Modes for carrying out the invention]

[0007] An example of an embodiment of the system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a processor with a reference number (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)), etc.

[0010] In the following embodiments, a RAM (Random Access Memory) with a reference number is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0011] In the following embodiments, a storage with a reference number is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0012] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0014] [First Embodiment]

[0015] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0016] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0018] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0019] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0021] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0022] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0024] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0026] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[0027] "Example of form 1"

[0028] The system of this invention provides a means for users to input their own experiences and future goals.

[0029] In essence, the system allows users to input their experiences and goals in text format through a user interface. For example, if a user inputs, "I have experience in project management, and in the future I would like to work on project management utilizing AI technology," this information will be saved in the system.

[0030] "Example of form 2"

[0031] Next, the personnel recommendation system recommends appropriate individuals within the group companies based on the input information. Specifically, it uses an AI algorithm to learn the characteristics of employees from their output and registers them in a database. For example, the AI ​​learns from an employee's past projects and achievements that the employee is proficient in AI technology and recommends that employee.

[0032] "Example of form 3"

[0033] Finally, the appointment scheduling method automatically sets up appointments with recommended individuals. Specifically, it sets up appointments such as one-on-one meetings according to the user's preferences. For example, if a user enters, "I would like to schedule a one-on-one appointment for next Monday," the system compares the schedules of the recommended individuals with the user's, finds a time that works for both parties, and sets up the appointment.

[0034] The following describes the processing flow for each example of the form.

[0035] "Example of form 1"

[0036] Step 1: The user enters their experience and future goals in text format through the system's user interface. For example, they might enter, "I have experience in project management, and in the future I would like to work on project management utilizing AI technology." Step 2: The entered information is saved in the system.

[0037] "Example of form 2"

[0038] Step 1: The personnel recommendation system uses an AI algorithm based on stored information to learn about individual characteristics from employee output.

[0039] Step 2: The learned characteristics are registered in the database.

[0040] Step 3: The AI ​​learns from an employee's past projects and achievements whether that employee is proficient in AI technology and recommends that employee.

[0041] "Example of form 3"

[0042] Step 1: The user enters "I would like to schedule a 1-on-1 appointment for next Monday."

[0043] Step 2: The appointment scheduling system compares the schedules of the recommended individuals with those of the user.

[0044] Step 3: Find a time that works for both parties and set up an appointment.

[0045] (Example 1)

[0046] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0047] Conventional systems struggled to provide appropriate advice based on user experience and goals, and in particular, they were unable to effectively utilize the generation of prompts and responses using generative AI models. As a result, they lacked sufficient concrete information to support users' career development.

[0048] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0049] In this invention, the server includes means for inputting the user's experiences and future goals, means for generating prompt sentences to be input to a generative AI model based on the relevant information, and means for sending the generated prompt sentences to the generative AI model and receiving a response. This makes it possible to utilize the generative AI model based on the user's input and provide the user with appropriate advice.

[0050] "A means of inputting user experiences and future goals" refers to a function that provides an interface for users to input their past experiences and future goals in text format.

[0051] "Means for generating prompt text to input into a generative AI model" refers to a function that analyzes user input data and creates prompt text to provide information to the generative AI model in the most optimal format.

[0052] "Means for sending generated prompt sentences to a generation AI model and receiving responses" refers to a communication function for sending generated prompt sentences to a generation AI model and receiving its responses.

[0053] "A means of providing appropriate advice to users" refers to a function that presents users with specific advice to support their career development, based on responses received from a generative AI model.

[0054] This invention is a system in which a user inputs their own experiences and future goals, and then utilizes a generated AI model to provide appropriate advice based on that input. The following describes a specific form for implementing this system.

[0055] Users access the user interface through a web browser or mobile application. This interface provides a means for users to input their experiences and goals in text format. For example, a user might input, "I have experience in project management, and in the future I would like to work on project management utilizing AI technology."

[0056] The terminal sends the data entered by the user to the server. Typically, this data is packaged in JSON format and sent as an HTTP request. The server parses the received data and generates prompts for input into the AI ​​model based on the user's input. Programming languages ​​such as Python and Java (registered trademark) are used for this process.

[0057] The generated prompt is sent to the AI ​​model. The server accesses the AI ​​model via an API and provides the prompt as input. For example, it can generate a prompt such as, "The user has project management experience and is interested in projects utilizing AI technology. What skills should they learn?"

[0058] Upon receiving a response from the generated AI model, the server provides appropriate advice to the user based on that information. This advice includes specific information to support the user's career development. The terminal displays the information received from the server in the user interface, allowing the user to view the advice and recommendations on the screen.

[0059] This system aims to provide users with specific and useful advice by utilizing a generated AI model based on user input.

[0060] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0061] Step 1:

[0062] The user inputs information. Users access the user interface via a web browser or mobile application and input their experiences and future goals in text format. The entered data is then transmitted to the device as information related to the user's career development.

[0063] Step 2:

[0064] The device sends data. The device converts the text data entered by the user into JSON format and sends it to the server as an HTTP request. This process verifies the format of the input data to maintain data integrity.

[0065] Step 3:

[0066] The server receives the data. The server receives the HTTP request sent from the terminal and extracts the user's input data from the request body. The server verifies the integrity of the data and checks for any invalid data.

[0067] Step 4:

[0068] The server generates prompt text. The server analyzes the received user data and generates prompt text to input into the AI ​​model. This process uses natural language processing techniques to appropriately summarize the user's input and format it as prompt text.

[0069] Step 5:

[0070] The server sends a prompt message to the generating AI model. The server sends the generated prompt message to the generating AI model via the API. The generating AI model receives the prompt message as input and generates advice regarding the user's career development.

[0071] Step 6:

[0072] The server receives the response from the generated AI model. The server receives the response from the generated AI model and analyzes its contents. The response includes specific advice and recommendations to support the user's career development.

[0073] Step 7:

[0074] The terminal displays the results to the user. The terminal displays the advice received from the server on the user interface. The user can review the advice and recommendations on the screen and use them to help with their future career development.

[0075] (Application Example 1)

[0076] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server," and the smart device 14 will be referred to as a "terminal."

[0077] In modern society, it is difficult to efficiently provide appropriate information based on the individual user's experiences and future goals. In particular, there is a demand for personalized information delivery that meets the diverse needs of users, but this is difficult to achieve with conventional systems. Therefore, there is a need for a system that generates relevant information based on user input and delivers it appropriately.

[0078] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0079] In this invention, the server includes means for inputting the user's experiences and future goals, generation means for generating relevant information based on the relevant information, and distribution means for delivering the generated information to the user. This enables the generation and delivery of information tailored to the individual needs of the user.

[0080] "A means of inputting user experiences and future goals" refers to a function that provides an interface for users to input their past experiences and future goals in text format.

[0081] "Generating means for generating related information based on relevant information" refers to a function that processes information entered by the user to generate related content and data.

[0082] "A means of delivering generated information to users" refers to a function that provides generated content and data to users in an appropriate format.

[0083] A "generative AI model" is an artificial intelligence model used to generate relevant information based on user input.

[0084] A "prompt statement" is an instruction given to a generative AI model, used to determine the content and format of the information that will be generated.

[0085] To implement this invention, an application installed on the user's device is used. The user uses a device such as a smartphone or tablet to input their experiences and future goals in text format. The entered information is sent to a server and stored in a database.

[0086] The server generates relevant information using a generative AI model based on the stored information. This generative AI model can use, for example, OpenAI's GPT. The generated information is selected according to the user's interests and needs and delivered to the user's device in an appropriate format.

[0087] For example, if a user enters "I am interested in project management using AI technology," the server will generate content such as "the latest trends in project management using AI" and "success stories of AI project management" and deliver it to the user.

[0088] An example of a prompt message is: "User experience: Project management. Goal: Project management using AI technology. Generate relevant content."

[0089] In this way, it becomes possible to generate and deliver information tailored to the individual needs of users.

[0090] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0091] Step 1:

[0092] The user launches an application on their device and enters their experiences and future goals in text format. The entered information is sent from the device to the server. The input data consists of text information about the user's experiences and goals.

[0093] Step 2:

[0094] The server stores the received user input information in a database. During this process, the input data is converted to an appropriate format before being stored in the database. The database also records each user's experience and goals.

[0095] Step 3:

[0096] The server uses a generative AI model to generate relevant information based on stored user information. Specifically, it inputs prompt statements into the generative AI model and generates relevant content. The input is the prompt statement, and the output is the generated content.

[0097] Step 4:

[0098] The server sorts the generated content according to the user's interests and needs. The sorted information is filtered to be useful to the user. The input is the generated content, and the output is the sorted content.

[0099] Step 5:

[0100] The server delivers the selected content to the user's device. The user can view the delivered information on their device. The input is the selected content, and the output is the information displayed on the user's device.

[0101] (Example 2)

[0102] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0103] In modern organizations, quickly and accurately finding the right people for a project is crucial, but selecting the right individuals from a vast amount of data is difficult. Furthermore, efficiently scheduling meetings with selected individuals is also a challenge.

[0104] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0105] In this invention, the server includes means for inputting the user's experience and future goals into an information processing device, means for recommending appropriate individuals within the organization based on the relevant information, and means for automatically setting up meetings with the recommended individuals. This makes it possible to quickly recommend the most suitable personnel for a project and efficiently set up meetings.

[0106] An "information processing device" is a device that receives input from a user and processes the data.

[0107] A "user" is an entity that uses a system to input information and obtain results.

[0108] "Experience" is a general term for the knowledge and skills a user has acquired in the past.

[0109] "Future goals" refer to the future state or outcome that the user hopes to achieve.

[0110] An "organization" is a group of members who come together to achieve a specific purpose.

[0111] A "personnel recommendation system" is a method for selecting appropriate individuals within an organization based on the information entered.

[0112] "Deliverables" is a general term for the results obtained from past work or projects undertaken by the team members.

[0113] An "information recording device" is a device that can store data and retrieve it as needed.

[0114] A "meeting scheduling mechanism" is a means for automatically scheduling meetings with recommended individuals.

[0115] A "private meeting" is a meeting held one-on-one with a specific person.

[0116] As an embodiment of this invention, the following system is constructed.

[0117] The server functions as an information processing device, receiving input from users. Users input their experiences and future goals through a terminal. Based on this information, the server performs a personnel recommendation system to recommend suitable individuals within the organization. This process involves using AI algorithms to learn characteristics from the deliverables of members and registering them in an information recording device. Specifically, machine learning frameworks such as TENSORFLOW® and PyTorch are used to analyze data and build models.

[0118] The terminal receives prompt messages from the user and sends them to the server. For example, a prompt message such as "Please recommend an employee who is proficient in AI technology" might be entered. Based on this prompt message, the server uses a pre-trained AI model to recommend the most suitable employee.

[0119] Furthermore, the server includes a meeting scheduling mechanism that automatically arranges meetings with recommended individuals. This allows users to efficiently find suitable personnel for their projects and quickly schedule necessary meetings. This system is expected to optimize talent utilization within organizations and improve project success rates.

[0120] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0121] Step 1:

[0122] Users input their experiences and future goals through their terminals. This information is sent to the server as foundational data to identify the skills and characteristics required for the project. The input information is transmitted to the server in text format.

[0123] Step 2:

[0124] The server uses the received user information to collect relevant data from the organization's member database. Specifically, it uses SQL queries to extract data on members' past projects and achievements. This data serves as input for analysis by AI algorithms.

[0125] Step 3:

[0126] The server preprocesses the collected data and converts it into a format usable by the AI ​​model. For example, it converts text data into numerical vectors and imputes missing values. This process uses data processing libraries such as Pandas and NumPy. The preprocessed data is then used as input for the AI ​​model.

[0127] Step 4:

[0128] The server runs an AI model using pre-processed data to identify members who meet the user's requirements. Specifically, it analyzes the data using a neural network model built with TensorFlow or PyTorch and recommends the most suitable individuals. This result is generated as a recommendation list.

[0129] Step 5:

[0130] The server sends the generated recommendation list to the terminal. The user reviews this list via the terminal and selects suitable personnel for the project. The recommendation list includes information such as the names, skills, and past achievements of the members.

[0131] Step 6:

[0132] The server automatically schedules meetings with individuals selected by the user. Specifically, it uses a calendar API to coordinate the schedules of the user and selected members and set up meetings. This allows users to efficiently schedule meetings and move projects forward.

[0133] (Application Example 2)

[0134] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0135] In modern organizations, quickly identifying the right people and assigning them to the right tasks is a critical challenge. However, traditional methods make it difficult to accurately understand the characteristics and skills of individual workers and select the most suitable individuals. Furthermore, it is difficult to monitor work progress in real time and reassign workers as needed. This can lead to decreased work efficiency and wasted resources.

[0136] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0137] In this invention, the server includes means for inputting the user's experience and future goals, means for recommending appropriate individuals within the organization based on the relevant information, means for automatically setting appointments with the recommended individuals, means for recommending the most suitable workers according to the work content, and means for analyzing the progress of work and the necessary skills in real time. This enables the optimal allocation of personnel within the organization, leading to improved work efficiency and effective use of resources.

[0138] "A means of inputting user experiences and future goals" refers to an interface for inputting data about individual users' past experiences and goals they wish to achieve in the future.

[0139] A "personnel recommendation system that recommends appropriate individuals within an organization based on relevant information" is an algorithm that analyzes the input information and selects and recommends the person within the organization who is most suitable for that information.

[0140] "An appointment scheduling method that automatically sets up appointments with recommended individuals" refers to a system that automatically adjusts and sets the date and time of meetings or interviews between recommended individuals and users.

[0141] "A means of recommending the most suitable worker according to the work content" refers to a function for selecting and recommending workers who possess the most suitable skills and experience for a particular task.

[0142] "Means for analyzing work progress and required skills in real time" refers to technologies for monitoring and analyzing the progress of work and the skills required for that work in real time.

[0143] To implement this invention, it is necessary to build a system in which a server plays a central role. The server provides an interface for users to input their experiences and future goals, and executes an AI algorithm to recommend suitable individuals within the organization based on the input information. Specifically, an AI model is built using a programming language such as Python, and a database management system (e.g., MySQL®) is used to manage the characteristics and skill sets of individuals within the organization.

[0144] The server uses a calendar API and other tools to adjust schedules and automatically set appointments with recommended individuals. It also analyzes work progress and required skills in real time to recommend the most suitable worker for each task. This requires software to collect and analyze data from sensors mounted on robots within the factory.

[0145] As a concrete example, if the installation of a specific part is delayed in the assembly process of a certain product, the server will recommend a worker who is familiar with that process. An example of a prompt to the generating AI model might be: "The installation of part Y is delayed in the assembly process of product X. Please recommend the most suitable worker for installing part Y."

[0146] In this way, the server enables the optimal allocation of personnel within the organization, improving work efficiency and making effective use of resources.

[0147] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0148] Step 1:

[0149] The server provides an interface for users to input their experiences and future goals. Users enter past projects and goals they wish to achieve. The entered data is sent to the server and stored in the database.

[0150] Step 2:

[0151] The server executes an AI algorithm to recommend suitable individuals within the organization based on the input information. The server retrieves the characteristics and skill sets of individuals within the organization from a database and compares them with the input information using a generative AI model. This allows it to select the most suitable individuals and generate a recommendation list.

[0152] Step 3:

[0153] The server automatically schedules appointments with recommended individuals. Using a calendar API, the server coordinates the schedules of both the recommended person and the user to select a suitable date and time. The selected date and time are then notified to both the user and the recommended person.

[0154] Step 4:

[0155] The server analyzes the progress of a task and the required skills in real time to recommend the most suitable worker for that task. The server collects data from sensors mounted on robots within the factory to evaluate the progress of the task. It compares the required skills with the skill sets of the workers to select the most suitable worker.

[0156] Step 5:

[0157] The server generates prompts for the AI ​​model and recommends workers as needed. For example, it generates a prompt such as, "The installation of part Y is delayed in the assembly process of product X. Please recommend the most suitable worker for installing part Y," and inputs it into the AI ​​model. This then recommends the most suitable worker.

[0158] (Example 3)

[0159] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0160] Traditional appointment scheduling systems required users to manually adjust schedules, which was time-consuming and laborious. Furthermore, the process of finding the right person was cumbersome, hindering efficient communication.

[0161] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0162] In this invention, the server includes means for inputting user requests in natural language, means for analyzing user requests using a generative AI model, and means for recommending appropriate individuals based on the analysis results. This enables users to efficiently set appointments and communicate quickly with appropriate individuals.

[0163] "A means of inputting user requests in natural language" refers to a function that provides an interface for users to input their desired appointment date, time, and format in natural language.

[0164] "Methods for analyzing user requests using generative AI models" refers to a function that uses generative AI models to analyze natural language requests entered by users and to identify specific appointment dates, times, and formats.

[0165] "Means for recommending appropriate individuals based on analysis results" refers to a function that selects and recommends the most suitable person based on the analyzed user requirements.

[0166] "Means of obtaining schedules with recommended individuals" refers to the function of using schedule management software to obtain schedule information of recommended individuals.

[0167] "A means of finding a time that works for both the user and the recommended person" refers to a function that compares the schedules of the user and the recommended person to find available time for both of them.

[0168] The "automatic appointment scheduling based on available time" feature is a function that automatically schedules appointments based on the availability of both the user and the recommended person.

[0169] A description of embodiments for carrying out this invention will be given.

[0170] Users enter their appointment preferences in natural language using their device. For example, they can enter specific dates, times, and formats, such as "I'd like to schedule a one-on-one appointment for next Monday." This input is done through a means of entering the user's request in natural language.

[0171] The server receives input from the user and performs analysis using a generative AI model. This analysis utilizes natural language processing technology to convert the user's request into a specific appointment date, time, and format. A general-purpose natural language processing model can be used as the generative AI model. An example of a prompt is, "Please suggest the best appointment date and time based on the user's preferences."

[0172] Based on the analysis results, the server recommends a suitable person. To obtain the recommended person's schedule, the server uses scheduling software. Specifically, it uses common scheduling software such as the Google® Calendar API to retrieve the schedule information of the user and the recommended person.

[0173] Based on the acquired schedule information, the server finds a time that is convenient for both the user and the recommended person. To automatically set an appointment at the found time, the server again uses the schedule management software and adds the appointment to the calendar. This series of processes allows the user to set appointments efficiently. The flow of the specific process in Example 3 will be explained using Figure 15.

[0174] Step 1:

[0175] The user enters their appointment preferences in natural language using a terminal. For example, they might enter a specific date, time, and format, such as, "I'd like to schedule a one-on-one appointment for next Monday." This input forms the basis for the next processing step.

[0176] Step 2:

[0177] The server passes the natural language input received from the user to a generative AI model. The generative AI model uses prompts to analyze the user's request. Specifically, it analyzes the input natural language to identify the date, time, and format of the appointment. This analysis result becomes the input for the next step.

[0178] Step 3:

[0179] The server recommends a suitable person based on the analysis results. Information about the recommended person is retrieved from the database. The server searches the database using the analysis results and selects the most suitable person. This recommendation result becomes the input for the next step.

[0180] Step 4:

[0181] The server uses scheduling software to retrieve the schedules of recommended individuals. Specifically, it uses the Google Calendar API to obtain schedule information for both the user and the recommended individuals. This schedule information will then be used as input for the next step.

[0182] Step 5:

[0183] The server uses the retrieved schedule information to find a time that works for both the user and the recommended person. The server compares their availability and determines the optimal appointment date and time. This determined date and time becomes the input for the next step.

[0184] Step 6:

[0185] The server automatically sets appointments based on the time it finds. The server uses the Google Calendar API to add appointments to the calendar at the determined date and time. This eliminates the need for users to manually adjust their schedules.

[0186] (Application Example 3)

[0187] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0188] In modern organizations, efficiently scheduling appointments with the right person at the user's preferred date and time is crucial. However, traditional systems often require manual processes of checking the schedules of individuals within the organization based on the user's preferred date and time, and finding available time slots, which is time-consuming and laborious. Furthermore, the lack of functionality to automatically add confirmed appointments to the user's and the organization's personnel's calendars makes appointment management cumbersome.

[0189] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0190] In this invention, the server includes means for inputting the user's experience and future goals; means for recommending appropriate individuals within the organization based on the relevant information; means for automatically setting appointments with the recommended individuals; means for inputting the user's desired date and time, checking the schedules of individuals within the organization, and suggesting available times; and means for automatically adding confirmed appointments to the calendars of the user and individuals within the organization. This makes it possible to efficiently set appointments at the date and time desired by the user and to automate appointment management.

[0191] A "user" is an individual or member of an organization who intends to use the system to schedule an appointment.

[0192] "Experience" refers to the knowledge, skills, and achievements a user has acquired in the past, and is a factor considered when setting up an appointment.

[0193] "Future goals" refer to specific objectives or plans that the user wishes to achieve, and are factors considered when setting up an appointment.

[0194] A "person recommendation system" is a function that selects and recommends appropriate individuals within an organization based on their experience and future goals.

[0195] The "appointment setting method" is a function that automatically sets appointments with recommended individuals based on the user's preferred date and time.

[0196] A "schedule" is a timetable that shows the planned activities and free time of individuals within an organization.

[0197] "Free time" refers to periods within an organization when a person does not have other appointments or activities, and is the time available for scheduling appointments.

[0198] A "schedule" is a tool for recording and managing the schedules of users and individuals within an organization.

[0199] The system for carrying out this invention comprises a user terminal and a server. The user terminal is a device such as a smartphone or tablet, which provides an interface for the user to input their experiences and future goals. The server receives input from the user and performs a person recommendation means for recommending individuals within the organization.

[0200] The server retrieves the characteristics of individuals within the organization from a database based on the user's input and recommends the appropriate person. In this process, a generative AI model is used to select the person best suited to the user's experience and goals.

[0201] To schedule an appointment with a recommended person, the server uses an appointment scheduling mechanism. When the user enters their preferred date and time, the server checks the schedules of individuals within the organization and suggests available times. This allows the user to efficiently schedule appointments.

[0202] Confirmed appointments are automatically added to the calendars of both the user and individuals within the organization by the server. This simplifies appointment management and makes it easier for both users and individuals within the organization to check their schedules.

[0203] For example, if a user enters "I would like to schedule an appointment with the person in charge for 3 PM next Wednesday," the server will check the person in charge's schedule, and if it confirms that 3 PM is available, it will notify the user and confirm the appointment.

[0204] An example of a prompt message would be, "I would like to schedule an appointment with the person in charge for 3 PM next Wednesday. Please check their availability and confirm the reservation."

[0205] In this way, users can efficiently schedule appointments at their desired time and time, and communicate smoothly with people within their organization.

[0206] The flow of the specific processing in Application Example 3 will be explained using Figure 16.

[0207] Step 1:

[0208] The user uses a device to enter their experience, future goals, and preferred appointment dates and times. The entered data is then sent from the device to the server.

[0209] Step 2:

[0210] The server initiates a process to recommend individuals within the organization based on the user's experience and goals. Using a generative AI model, it analyzes the user's input data and retrieves the characteristics of suitable individuals from the database. This allows it to select the person best suited to the user.

[0211] Step 3:

[0212] The server checks the schedules of individuals within the organization based on the user's preferred date and time to set up an appointment with the recommended person. It uses a schedule management API to retrieve the person's availability and matches it with the user's preferred date and time.

[0213] Step 4:

[0214] The server suggests available time slots to the user when it finds them. Once the user accepts the suggested time, the server confirms the appointment and automatically adds it to the user's and other relevant individuals' calendars. This streamlines appointment management.

[0215] Step 5:

[0216] The server sends notifications to the user and relevant individuals within the organization regarding confirmed appointments. The notification system is used to send messages containing appointment details, allowing both parties to confirm their schedules.

[0217] In this way, users can efficiently schedule appointments at their desired dates and times, and communicate smoothly with people within their organization.

[0218] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0219] "Example of form 1"

[0220] One embodiment of the present invention involves a system that includes an emotion engine that recognizes the user's emotions as a means of inputting the user's experiences and future goals. This emotion engine analyzes emotions from the user's text or voice input and feeds the results back to the system. For example, if a user inputs, "I have experience in project management, and in the future I would like to work on project management utilizing AI technology," the emotion engine reads the user's motivation and expectations from that text.

[0221] "Example of form 2"

[0222] Furthermore, some systems recommend individuals by taking into account the user's emotions, as recognized by an emotion engine. In this system, the emotion engine analyzes the results to infer what kind of people the user wants to interact with, and then recommends individuals based on that. For example, if the user shows positive emotions, the system will recommend individuals who are also positive.

[0223] "Example of form 3"

[0224] Furthermore, some appointment scheduling systems take into account the user's emotions, as recognized by an emotion engine. This system considers the user's emotional state and schedules appointments at a time and format appropriate to that state. For example, if a user is feeling stressed, the system might schedule an appointment during a time when they can relax.

[0225] The following describes the processing flow for each example of the form.

[0226] "Example of form 1"

[0227] Step 1: The user enters their experiences and future goals into the system via text or voice input.

[0228] Step 2: The emotion engine analyzes the user's emotions from their input. This analysis utilizes natural language processing and speech analysis technologies.

[0229] Step 3: The emotion engine feeds the analysis results back into the system. This feedback includes the user's emotional state and its intensity.

[0230] "Example of form 2"

[0231] Step 1: The emotion engine analyzes the user's emotions.

[0232] Step 2: Based on the analysis results of the emotion engine, the system infers what kind of people the user wants to interact with.

[0233] Step 3: Based on the prediction results, the system recommends a suitable person to the user.

[0234] "Example of form 3"

[0235] Step 1: The emotion engine analyzes the user's emotions.

[0236] Step 2: Based on the analysis results of the emotion engine, the system determines the appropriate timing and format for the user's emotional state.

[0237] Step 3: The system sets an appointment based on its assessment results.

[0238] (Example 1)

[0239] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0240] Traditional systems could recommend the right person and schedule appointments based on the user's experience and goals, but they couldn't provide feedback that took the user's emotions into account. As a result, there was a lack of support that reflected the user's motivation and expectations.

[0241] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0242] In this invention, the server includes means for the user to input their experiences and future goals, means for recommending appropriate individuals within the group based on the relevant information, means for automatically setting appointments with the recommended individuals, means for analyzing the user's input information and recognizing their emotions, and means for providing feedback to the user based on the analysis results. This enables the provision of appropriate feedback that takes the user's emotions into consideration and supports the user in achieving their goals.

[0243] "A means for users to input experiences and future goals" refers to a device or software that provides an interface for users to input their past experiences and future goals in text format.

[0244] A "person recommendation system" is an algorithm or system that identifies and recommends appropriate individuals within a group based on information entered by the user.

[0245] An "appointment setting tool" is a device or software that has the function of automatically scheduling meetings or interviews with recommended individuals.

[0246] "Emotion analysis means" refers to a technology or system that analyzes user input information to recognize the user's emotions and motivations.

[0247] A "feedback tool" is a device or software that has the function of providing appropriate advice or information to the user based on the results of sentiment analysis.

[0248] This invention is a system that provides an interface for users to input their experiences and future goals. Users can input information in text format using a dedicated application on their terminal or a web browser. The input information is transmitted from the terminal to the server.

[0249] The server stores the received information in a database. This database can use a common relational database management system (RDBMS) such as MySQL or PostgreSQL. The stored information is analyzed by a person recommendation system to identify and recommend suitable individuals to the user.

[0250] Furthermore, the server uses sentiment analysis tools to analyze the user's emotions from their input information. This analysis utilizes an emotion engine that leverages natural language processing (NLP) technology. Specifically, services such as Google Cloud Natural Language API and IBM Watson® Natural Language Understanding can be used.

[0251] The analysis results are provided to the user through a feedback mechanism. This feedback is sent to the user's device as advice and support information to help them achieve their goals. The user can then review the feedback on their device and use it to guide their next actions.

[0252] For example, if a user enters "I have experience in project management and would like to work on project management using AI technology in the future," the sentiment analysis tool will read the user's motivation and expectations from that text, and the feedback tool will provide advice based on that.

[0253] An example of a prompt for a generative AI model is, "Analyze the user's input to understand their motivation and expectations, and generate feedback." By using this prompt, the AI ​​model can generate feedback that takes the user's emotions into account.

[0254] The flow of the specific processing in Example 1 will be explained using Figure 17.

[0255] Step 1:

[0256] Users access the user interface via a dedicated application or web browser using their device. Users enter their experiences and future goals into text boxes. Once they have finished entering the data, they click the "Submit" button, sending the data from their device to the server. The input data consists of text information about the user's experiences and goals.

[0257] Step 2:

[0258] The server receives user input data sent from the terminal. The received data is stored in the database. The server establishes a database connection and executes SQL queries to save the user input data. The input is the user's text information, and the output is the information stored in the database.

[0259] Step 3:

[0260] The server passes stored user input data to the sentiment analysis tool. The sentiment analysis tool uses natural language processing technology to analyze emotions from the text. The server sends an API request to the sentiment engine and receives the analysis results. The input is text information obtained from the database, and the output is the analysis result regarding the user's emotions.

[0261] Step 4:

[0262] The server provides feedback to the user using a feedback mechanism based on the analysis results obtained from the sentiment analysis mechanism. The server generates a feedback message based on the analysis results and sends it to the terminal. The user can view the feedback message on the terminal. The input is the result of the sentiment analysis, and the output is the feedback message provided to the user.

[0263] (Application Example 1)

[0264] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server," and the smart device 14 will be referred to as a "terminal."

[0265] In today's information society, it is crucial to recommend appropriate people and products based on users' experiences and future goals. However, conventional systems often fail to consider user emotions when making recommendations, making it difficult to meet user expectations.

[0266] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0267] In this invention, the server includes means for inputting the user's experiences and future goals, means for recommending appropriate individuals within the group organization based on the relevant information, means for automatically setting appointments with the recommended individuals, means for analyzing the user's input information and emotions, and means for recommending products based on the analysis results. This enables personalized recommendations that take the user's emotions into consideration.

[0268] "Means for inputting user experiences and future goals" refers to a feature that provides an interface for users to input their past experiences and future goals in text or voice.

[0269] "Person recommendation methods" are functions that identify and recommend appropriate individuals within a group organization based on user input information.

[0270] The "appointment scheduling method" is a function that automatically schedules meetings and interviews with recommended individuals.

[0271] "Emotion analysis tools" are functions that analyze user input information to evaluate the user's emotions and motivation.

[0272] A "product recommendation method" is a function that selects and recommends the most suitable product to the user based on the results of sentiment analysis.

[0273] The system for implementing this invention consists of a terminal equipped with an interface for inputting the user's experiences and future goals, and a server that analyzes the input information. The terminal is a device such as a smartphone or computer, and allows the user to input information in text or voice. The server uses software such as Python or TensorFlow to analyze the user's input information with a natural language processing library (such as NLTK) and perform sentiment analysis.

[0274] The server has a product recommendation engine for recommending the most suitable products to the user based on the results of sentiment analysis. This engine selects relevant products considering the user's purchasing intention and anticipation. Furthermore, the server also has a function of recommending appropriate people within the group organization based on the user's input information and automatically setting appointments.

[0275] As a specific example, when the user uses the terminal to input "Recently interested in fitness and looking for fitness-related gadgets", the server analyzes this information and determines that the user's interest is high. Based on this, it recommends fitness bands and smartwatches. Also, when the user inputs "Have experience in project management and want to engage in project management using AI technology in the future", the server recommends appropriate experts and sets an appointment for an interview.

[0276] An example of the prompt text input to the generative AI model is "Analyze the user's input text and recommend products that can enhance the purchasing intention. Input: 'Recently interested in fitness and looking for fitness-related gadgets'".

[0277] The flow of the specific process in Application Example 1 will be described using FIG. 18.

[0278] Step 1:

[0279] The user uses the terminal to input their experience and future goals in text or voice. The input data is sent from the terminal to the server. The input data includes information about the user's interests and goals.

[0280] Step 2:

[0281] The server analyzes the received input data using a natural language processing library (such as NLTK). As a result, the user's intention and sentiment are extracted. Specifically, text tokenization, part-of-speech tagging, and sentiment score calculation are performed.

[0282] Step 3:

[0283] The server uses a generative AI model to select the most suitable products for the user based on the results of sentiment analysis. It uses sentiment scores as input, and the product recommendation engine lists relevant products. The output is a list of products that match the user's interests.

[0284] Step 4:

[0285] The server recommends appropriate individuals within the group organization based on user input. Using the user's goals and experience as input, the person recommendation engine identifies suitable experts. The output is information about the recommended individuals.

[0286] Step 5:

[0287] The server automatically schedules appointments with recommended individuals. Using the recommended person's information and the user's preferred date and time as input, the scheduling algorithm determines the optimal date and time. The output is the details of the scheduled appointment.

[0288] (Example 2)

[0289] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0290] In modern organizations, it is crucial to recommend the right person quickly and accurately, but traditional systems struggle to adequately consider users' feelings and preferences when making recommendations. Furthermore, scheduling appointments with recommended individuals is often done manually, hindering efficient talent utilization.

[0291] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0292] In this invention, the server includes means for inputting user information, means for recommending appropriate individuals within the organization based on the relevant information, means for automatically setting appointments with the recommended individuals, means for analyzing the user's emotions, and means for recommending individuals based on the analysis results. This enables the recommendation of appropriate personnel that takes into account the user's emotions and wishes, and efficient appointment setting.

[0293] "Means for inputting user information" refers to an interface that allows users to input their own information and desired conditions into the system.

[0294] A "person recommendation system" refers to an algorithm or process that identifies and recommends suitable individuals within an organization based on the information entered.

[0295] The "appointment scheduling method" is a function that automatically schedules meetings and interviews with recommended individuals.

[0296] "Methods for analyzing user emotions" refer to analytical techniques that identify a user's emotional state based on their input data.

[0297] "A method for recommending individuals based on analysis results" refers to a process for recommending the most suitable individuals by taking into account the results of the user's sentiment analysis.

[0298] "Methods for learning individual characteristics from the deliverables of members" refers to techniques for learning the characteristics and skills of individuals by analyzing the deliverables of tasks and projects that members of an organization have performed in the past.

[0299] An "information recording device" is a database or storage system used to save the characteristics and skills of a person that have been learned.

[0300] An "individual interview" is a form of interview or meeting conducted one-on-one between the user and the recommended person.

[0301] The embodiments for implementing this invention will be described.

[0302] The server provides an interface for users to input information. Through this interface, users can input their own information and desired conditions. The input information is stored in the database within the server.

[0303] The server uses an AI algorithm as a person recommendation means. This algorithm analyzes the achievements of members using machine learning frameworks such as TensorFlow and PyTorch, and learns the characteristics of each person. The learned characteristics are registered in the information recording device.

[0304] The terminal uses emotion analysis APIs of Affectiva and Microsoft (registered trademark) Azure (registered trademark) to analyze the emotions of users. Based on the text and voice data input by the user, the current emotional state is identified. The analysis results are sent to the server.

[0305] The server executes a means to recommend a person based on the analysis results. As a result, the person most suitable for the user's desired conditions and emotional state can be identified and recommended.

[0306] Furthermore, the server uses appointment setting means to automatically set up interviews and meeting schedules with the recommended person. Through this process, the user can efficiently contact appropriate talents.

[0307] As a specific example, when a user inputs a prompt sentence such as "Please recommend the most suitable employees for the AI project. I am motivated.", the server analyzes the employee data using an AI algorithm and lists up motivated AI engineers. This list is displayed on the user's terminal, and the user can select the most suitable employee from it.

[0308] The flow of the specific process in Embodiment 2 will be described using FIG. 19.

[0309] Step 1:

[0310] Users input their information and preferences through the system interface. This information is sent to the server and stored in a database. This includes project type and required skill set.

[0311] Step 2:

[0312] The server collects data from a database regarding the past projects and achievements of members within the organization. Based on the collected data, an AI algorithm using TensorFlow or PyTorch learns the characteristics of each member. Through this process, the skills and characteristics of each member are registered in the information recording device.

[0313] Step 3:

[0314] The device uses Affectiva or Microsoft Azure sentiment analysis APIs to analyze the user's emotions. Based on text and voice data entered by the user, it identifies the current emotional state. The analysis results are sent to the server as data indicating the user's emotional state.

[0315] Step 4:

[0316] The server executes an AI algorithm based on the user's preferences and sentiment analysis results. This identifies the most suitable members for the user's criteria and generates a recommendation list. The recommendation list takes into account the user's preferences and emotional state.

[0317] Step 5:

[0318] The server presents the generated recommendation list to the user. The user can then select project members based on this list. Specifically, the list displays the member's name, skill set, and past achievements.

[0319] Step 6:

[0320] The server automatically schedules appointments with selected members. Using the appointment scheduling mechanism, it efficiently coordinates interview and meeting schedules and notifies the user. This allows the user to quickly connect with the appropriate personnel.

[0321] (Application Example 2)

[0322] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0323] In modern manufacturing environments, proper personnel allocation and team formation are crucial for improving production efficiency. However, traditional methods have made it difficult to recommend personnel that fully consider the characteristics and emotional states of workers, thus hindering the creation of optimal teams. This has resulted in challenges such as decreased production efficiency and reduced worker motivation.

[0324] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0325] In this invention, the server includes means for inputting the user's experience and future goals, means for recommending appropriate individuals within the organization based on the relevant information, means for automatically setting appointments with the recommended individuals, means for learning the characteristics of workers and registering them in a database, and means for considering the user's emotional state using emotion analysis means and recommending the most suitable person. This enables optimal personnel placement and team formation that takes into account the characteristics and emotional state of workers.

[0326] "A means of inputting user experiences and future goals" refers to an interface that allows users to input their past experiences and future goals into the system.

[0327] A "person recommendation system" is a function that includes an algorithm for selecting and recommending appropriate individuals within an organization based on the information entered.

[0328] The "appointment scheduling method" is a function that automatically adjusts and sets the date and time for meetings or interviews with recommended individuals.

[0329] "Methods for learning worker characteristics and registering them in a database" refers to the process by which AI analyzes workers' past performance and skills and saves the results in a database.

[0330] "Emotional analysis means" refers to technology that analyzes a user's current emotional state and reflects the results in person recommendations.

[0331] The system for carrying out this invention includes a server, a user terminal, and a database. The server provides an interface for users to input their experiences and future goals, and recommends appropriate individuals within the organization based on the input information. The server uses an AI algorithm to learn the characteristics of workers and registers them in the database. Furthermore, it uses sentiment analysis means to analyze the user's emotional state and reflects the results in person recommendations.

[0332] The server implements AI algorithms using Python and utilizes the OpenAI API for sentiment analysis. The database stores data on workers' skills, past performance, and emotional states. The user terminal receives recommendation results from the server and automatically sets up appointments with the recommended individuals.

[0333] As a concrete example, when setting up a new production line in a factory, the server identifies workers who have performed well in past projects, confirms that their current emotional state is motivated, and recommends them as leaders. An example of a prompt to input into the generative AI model would be, "Recommend the best worker to set up the new production line. Please consider past performance and current emotional state."

[0334] The flow of a specific process in Application Example 2 will be explained using Figure 20.

[0335] Step 1:

[0336] The user uses a terminal to input their experiences and future goals. The entered information is sent to the server. The server receives this information and stores it in a database.

[0337] Step 2:

[0338] The server uses an AI algorithm to recommend suitable individuals within the organization based on user information stored in the database. The AI ​​algorithm analyzes the worker's past performance and skills to select the person best suited to the user's goals. The output of this process is a list of recommended individuals.

[0339] Step 3:

[0340] The server analyzes the user's emotional state using emotion analysis tools. Based on the user's input information and past data, it infers their current emotional state. The analysis results are reflected in the person recommendation. Specifically, users who show motivated emotions will be recommended similarly motivated individuals.

[0341] Step 4:

[0342] The server automatically sets up appointments with recommended individuals. It selects the optimal date and time, taking into account the user's schedule and preferences. The scheduled appointment information is sent to the user's terminal, and the user is notified.

[0343] Step 5:

[0344] Users can view recommendation results and appointment information through their terminal. They can change or cancel appointments as needed. The server updates the database in response to user actions and sends notifications to relevant individuals.

[0345] (Example 3)

[0346] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0347] Traditional systems may increase the user's psychological burden by scheduling appointments without considering their emotional state. Furthermore, they may not adequately reflect the user's experience and goals when recommending appropriate individuals. This presents a challenge in providing users with optimal communication opportunities.

[0348] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0349] In this invention, the server includes means for inputting the user's experiences and future goals, means for recommending appropriate individuals within the organization based on the relevant information, means for automatically setting appointments with the recommended individuals, means for analyzing the user's emotional state, and means for determining the optimal appointment time based on the emotional state. This makes it possible to provide optimal communication opportunities that take the user's emotional state into consideration.

[0350] "A means of inputting user experiences and future goals" refers to a function that provides an interface for users to input their past experiences and future goals into the system.

[0351] "Personnel recommendation methods" refer to algorithms and processes that select and recommend appropriate individuals within an organization based on user input information.

[0352] The "scheduling method" is a function that automatically coordinates and sets schedules with recommended individuals.

[0353] "Emotional analysis methods" are technologies that analyze a user's input data and past behavior to infer their current emotional state.

[0354] "Methods for determining the optimal appointment time based on emotional state" refers to a process that takes into account the user's emotional state and selects the optimal time to reduce psychological burden.

[0355] As an embodiment of this invention, the following system is constructed.

[0356] Users input their experiences and future goals through a terminal. This allows the system to understand the user's needs and desires. The entered information is sent to a server and stored in a database.

[0357] The server recommends suitable individuals within the organization based on information received from the user. As a means of recommending individuals, the server utilizes characteristic information of members registered in a database. This makes it possible to select the person best suited to the user's needs.

[0358] Next, the server uses scheduling software such as the Google Calendar API to automatically schedule appointments with recommended individuals. When a user enters a prompt such as, "I'd like to schedule a 1-on-1 appointment for next Monday," the server compares the user's and the recommended individuals' schedules, finds a common time slot, and schedules the appointment.

[0359] Furthermore, the server uses a generative AI model to analyze the user's emotional state. This emotional analysis tool analyzes the user's input data and past behavior to infer their current emotional state. For example, if the server determines that the user is experiencing stress, it uses this information to select the optimal time to alleviate their psychological burden and schedule activities accordingly.

[0360] In this way, users can obtain the optimal communication opportunity that takes their own emotional state into consideration. The flow of the specific processing in Example 3 will be explained using Figure 21.

[0361] Step 1:

[0362] Users input their experiences and future goals through their terminal. The entered information is sent to the server as prompt messages. For example, specific requests such as "I would like to schedule a one-on-one appointment for next Monday" might be entered. This input data is used as foundational data to understand the user's needs.

[0363] Step 2:

[0364] The server analyzes the prompt received from the user and recommends the appropriate person within the organization. The server accesses a database and, based on member characteristics, selects the person best suited to the user's needs. This process analyzes the user's input data and generates a list of recommended individuals.

[0365] Step 3:

[0366] The server uses the Google Calendar API to retrieve the schedules of the user and the recommended person. The server compares the schedules of both parties to find common free time. In this step, the schedule data is analyzed to determine the best time for the appointment.

[0367] Step 4:

[0368] The server uses a generative AI model to analyze the user's emotional state. Based on the user's input data and past behavior, the emotion analysis tool infers the user's current emotions. For example, if it determines that the user is feeling stressed, this information is taken into consideration in the next step.

[0369] Step 5:

[0370] The server determines the optimal appointment time based on the user's emotional state. To reduce psychological burden, it selects a time when the user can relax. This step takes into account the results of the emotional analysis to select the optimal time.

[0371] Step 6:

[0372] The server notifies the user and the recommended person of the details of the confirmed appointment. The notification is sent via email or calendar reminder. This allows the user and the recommended person to check the appointment details and have an opportunity to communicate.

[0373] (Application Example 3)

[0374] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0375] In today's business environment, communication that takes into account the user's emotional state is essential. However, traditional appointment scheduling systems fail to consider user emotions, making it difficult to schedule appointments at the optimal time. This can lead to decreased user satisfaction and hinder efficient communication.

[0376] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0377] In this invention, the server includes means for inputting the user's experience and future goals, means for recommending appropriate individuals within the organization based on the relevant information, means for automatically setting appointments with the recommended individuals, and means for recognizing the user's emotional state and adjusting the timing of appointments based on that emotional state. This makes it possible to set appointments at the optimal timing according to the user's emotional state, thereby improving user satisfaction.

[0378] A "user" is an individual or group that uses the system to schedule an appointment.

[0379] "Experience" is a general term for the knowledge, skills, and experiences a user has acquired in the past.

[0380] "Future goals" refer to the future plans and objectives that the user hopes to achieve.

[0381] "Means of input" refers to the methods or devices that users use to provide information to a system.

[0382] "Within the organization" refers to the internal workings of a specific company or group.

[0383] The "right person" is the individual who best matches the user's requirements and conditions.

[0384] A "recommendation method for recommending individuals" refers to a method or device for selecting and suggesting the most suitable person based on user information.

[0385] An "appointment" is a reservation for a meeting or conference at a specific date and time.

[0386] An "automatic appointment scheduling method" refers to a method or device for a system to automatically determine appointments based on user conditions.

[0387] "Emotional state" refers to the user's psychological state or mood.

[0388] "Emotion recognition means for recognizing and adjusting appointment timing based on the emotional state" refers to a method or device for analyzing a user's emotions and determining the optimal appointment time based on the results.

[0389] The system for carrying out this invention includes a terminal for inputting the user's experience and future goals, a server for recommending appropriate individuals within the organization, and a server for automatically scheduling appointments with the recommended individuals. Furthermore, it includes emotion recognition means for recognizing the user's emotional state and adjusting the timing of appointments based on that emotional state.

[0390] The server receives information entered by the user through the terminal and analyzes the user's emotional state using a generative AI model. During this process, it uses an emotion recognition API (e.g., Microsoft Azure Emotion API) to identify the user's emotions. Next, the server uses scheduling software (e.g., Google Calendar API) to retrieve the availability of appropriate individuals within the organization.

[0391] The server calculates the optimal appointment timing based on the user's emotional state and sets the appointment accordingly. This process allows for appointment scheduling at a time that suits the user's emotional state, thereby improving user satisfaction.

[0392] For example, if a user enters "I'd like to discuss security next Monday" into their device, the server uses an emotion recognition API to analyze the user's stress level. If the server determines that the stress level is high, it checks the availability of a support staff member and schedules an appointment for a more relaxed afternoon time.

[0393] An example of a prompt message would be, "If the user is feeling stressed, please tell me how to schedule an appointment during a time when they can relax."

[0394] The flow of the specific processing in Application Example 3 will be explained using Figure 22.

[0395] Step 1:

[0396] The user enters their experience, future goals, and desired appointment date and time via a terminal. The entered data is sent to the server. The server receives this data and prepares to analyze the user's request.

[0397] Step 2:

[0398] The server uses an emotion recognition API to analyze the user's emotional state. The input includes user voice and text data. The API processes this data and outputs the user's emotional state (e.g., stress level). Based on this output, the server understands the user's current emotional state.

[0399] Step 3:

[0400] The server runs a person recommendation algorithm that considers the user's input data and emotional state to recommend the right person within the organization. The inputs used are the user's experience, goals, and emotional state. The algorithm processes this data and outputs the most suitable person. Based on this output, the server identifies the recommended person.

[0401] Step 4:

[0402] The server uses scheduling software to retrieve the availability of the recommended person. The input includes the recommended person's ID and schedule information. The software processes this data and outputs their availability. Based on this output, the server identifies potential appointment times.

[0403] Step 5:

[0404] The server calculates the optimal appointment timing based on the user's emotional state. The inputs used are the user's emotional state and the availability of the recommended person. The server processes this data and outputs the optimal appointment time. Based on this output, the server automatically schedules the appointment.

[0405] Step 6:

[0406] The server notifies the user and the recommended person of the details of the scheduled appointment. The inputs used are the date, time, location, and participant information of the appointment. The server processes this data and outputs a notification message. The user and the recommended person receive this notification and confirm the appointment details.

[0407] (Other examples)

[0408] Next, other embodiments will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0409] In modern society, it is crucial for individual users to receive appropriate advice based on their own experiences and future goals. However, it is difficult and time-consuming for users to gather and analyze information on their own to determine the optimal course of action. Therefore, there is a need for a system that allows users to easily obtain specific advice related to their goals.

[0410] The identification process performed by the identification processing unit 290 of the data processing device 12 in other embodiments is realized by the following means.

[0411] In this invention, the server includes means for providing an interface for inputting the user's experiences and future goals, means for analyzing the input information and generating prompts to instruct a generative AI model to perform specific processes, and means for sending the generated prompts to the generative AI model and receiving responses. This makes it easy for the user to obtain specific and useful advice related to their goals.

[0412] "User experience and future goals" refers to the knowledge and skills a user has acquired so far, as well as the specific goals and visions they hope to achieve in the future.

[0413] An "interface" refers to a software component that provides an operating environment, such as a screen or form, that a user uses to input information.

[0414] "Analysis" refers to data processing techniques used to process information entered by users and extract important keywords and phrases.

[0415] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to generate responses in natural language based on a given prompt.

[0416] A "prompt" refers to a text-based instruction generated to tell a generative AI model to perform a specific action.

[0417] "Response" refers to the natural language output generated by the generative AI model based on the prompt.

[0418] "Advice" refers to specific action guidelines and suggestions for achieving goals, provided to the user based on responses from the generated AI model.

[0419] This invention is a system for users to receive appropriate advice based on their own experiences and future goals. The system consists of the user's terminal, a server, and a generative AI model.

[0420] Users access a dedicated interface using a web browser on their device. This interface, built with HTML and JavaScript (registered trademark), provides a form where users can input their experiences and future goals. For example, a user might enter a goal such as "I want to become a data scientist in the future" and click the submit button.

[0421] The server receives data sent from the user's terminal. The received data is sent to the server in JSON format. The server analyzes the received data using spaCy, a natural language processing library implemented in Python. Through this analysis, important keywords such as "data scientist" and "future" are extracted from the user's input.

[0422] Next, the server generates prompt messages based on the extracted keywords to instruct the generated AI model to perform specific actions. Specifically, it might create prompt messages such as, "The user wants to become a data scientist in the future. Please suggest the necessary skills and steps."

[0423] The generated prompt text is sent to a generative AI model such as OpenAI's GPT-3®. The server sends this prompt text to the AI ​​model's API via an HTTP request and receives a response. The AI ​​model generates appropriate advice based on the prompt text and returns it to the server.

[0424] The server analyzes the received response and prepares data for visual display to the user. The terminal receives the data sent from the server and displays advice to the user in a web browser. This display is visually formatted using HTML and CSS.

[0425] Example prompt: "The user wants to become a data scientist in the future. Please suggest the necessary skills and steps."

[0426] In this way, the system utilizes a generated AI model based on user input to provide users with specific and useful advice.

[0427] The flow of specific processing in other embodiments will be explained using Figure 23.

[0428] Step 1:

[0429] The user accesses a dedicated interface using a web browser on their device. The user fills in information in a form to enter their experiences and future goals, and then clicks the submit button. The entered information is sent to the server in JSON format.

[0430] Step 2:

[0431] The server receives JSON data sent from the user's terminal. The received data contains text information about the user's experiences and goals. The server analyzes the received data using spaCy, a natural language processing library implemented in Python. Through this analysis, it extracts important keywords such as "data scientist" and "future" from the user's input.

[0432] Step 3:

[0433] The server generates a prompt message based on the extracted keywords, instructing the generating AI model to perform a specific action. Specifically, it creates a prompt message that reads, "The user wants to become a data scientist in the future. Please suggest the necessary skills and steps." This prompt message is then ready to be sent to the generating AI model.

[0434] Step 4:

[0435] The server sends the generated prompt message to a generative AI model such as OpenAI's GPT-3. This transmission is done via an HTTP request. The server sends the prompt message to the AI ​​model's API endpoint and waits for a response from the AI ​​model.

[0436] Step 5:

[0437] The server receives a response from the generated AI model. The response includes specific advice related to the user's goals. For example, "To become a data scientist, it is important to hone your skills in Python and R and participate in data analysis projects."

[0438] Step 6:

[0439] The server analyzes the received response and prepares data for visual display to the user. The terminal receives the data sent from the server and displays advice to the user in a web browser. This display is visually formatted using HTML and CSS. Based on the advice provided, the user can consider their next steps.

[0440] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0441] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0442] Other examples of generative AI include Gemini® (registered trademark) (Internet search). <url: https: gemini.google.com ?hl="ja">) are some examples.

[0443] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0444] [Second Embodiment]

[0445] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0446] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0447] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0448] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0449] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0450] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0451] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0452] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0453] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0454] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0455] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0456] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[0457] "Example of form 1"

[0458] The system of the present invention provides a means for users to input their own experiences and future goals. Specifically, it allows users to input their experiences and goals in text format through a user interface. For example, if a user inputs "I have experience in project management and in the future I would like to work on project management utilizing AI technology," this information is stored in the system.

[0459] "Example of form 2"

[0460] Next, the personnel recommendation system recommends appropriate individuals within the group companies based on the input information. Specifically, it uses an AI algorithm to learn the characteristics of employees from their output and registers them in a database. For example, the AI ​​learns from an employee's past projects and achievements that the employee is proficient in AI technology and recommends that employee.

[0461] "Example of form 3"

[0462] Finally, the appointment scheduling method automatically sets up appointments with recommended individuals. Specifically, it sets up appointments such as one-on-one meetings according to the user's preferences. For example, if a user enters, "I would like to schedule a one-on-one appointment for next Monday," the system compares the schedules of the recommended individuals with the user's, finds a time that works for both parties, and sets up the appointment.

[0463] The following describes the processing flow for each example of the form.

[0464] "Example of form 1"

[0465] Step 1: The user enters their experience and future goals in text format through the system's user interface. For example, they might enter, "I have experience in project management, and in the future I would like to work on project management utilizing AI technology." Step 2: The entered information is saved in the system.

[0466] "Example of form 2"

[0467] Step 1: The personnel recommendation system uses an AI algorithm based on stored information to learn about individual characteristics from employee output.

[0468] Step 2: The learned characteristics are registered in the database.

[0469] Step 3: The AI ​​learns from an employee's past projects and achievements whether that employee is proficient in AI technology and recommends that employee.

[0470] "Example of form 3"

[0471] Step 1: The user enters "I would like to schedule a 1-on-1 appointment for next Monday."

[0472] Step 2: The appointment scheduling system compares the schedules of the recommended individuals with those of the user.

[0473] Step 3: Find a time that works for both parties and set up an appointment.

[0474] (Example 1)

[0475] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0476] Conventional systems struggled to provide appropriate advice based on user experience and goals, and in particular, they were unable to effectively utilize the generation of prompts and responses using generative AI models. As a result, they lacked sufficient concrete information to support users' career development.

[0477] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0478] In this invention, the server includes means for inputting the user's experiences and future goals, means for generating prompt sentences to be input to a generative AI model based on the relevant information, and means for sending the generated prompt sentences to the generative AI model and receiving a response. This makes it possible to utilize the generative AI model based on the user's input and provide the user with appropriate advice.

[0479] "A means of inputting user experiences and future goals" refers to a function that provides an interface for users to input their past experiences and future goals in text format.

[0480] "Means for generating prompt text to input into a generative AI model" refers to a function that analyzes user input data and creates prompt text to provide information to the generative AI model in the most optimal format.

[0481] "Means for sending generated prompt sentences to a generation AI model and receiving responses" refers to a communication function for sending generated prompt sentences to a generation AI model and receiving its responses.

[0482] "A means of providing appropriate advice to users" refers to a function that presents users with specific advice to support their career development, based on responses received from a generative AI model.

[0483] This invention is a system in which a user inputs their own experiences and future goals, and then utilizes a generated AI model to provide appropriate advice based on that input. The following describes a specific form for implementing this system.

[0484] Users access the user interface through a web browser or mobile application. This interface provides a means for users to input their experiences and goals in text format. For example, a user might input, "I have experience in project management, and in the future I would like to work on project management utilizing AI technology."

[0485] The terminal sends the data entered by the user to the server. Typically, this data is packaged in JSON format and sent as an HTTP request. The server parses the received data and generates prompts for input into the AI ​​model based on the user's input. Programming languages ​​such as Python and Java are used for this process.

[0486] The generated prompt is sent to the AI ​​model. The server accesses the AI ​​model via an API and provides the prompt as input. For example, it can generate a prompt such as, "The user has project management experience and is interested in projects utilizing AI technology. What skills should they learn?"

[0487] Upon receiving a response from the generated AI model, the server provides appropriate advice to the user based on that information. This advice includes specific information to support the user's career development. The terminal displays the information received from the server in the user interface, allowing the user to view the advice and recommendations on the screen.

[0488] This system aims to provide users with specific and useful advice by utilizing a generated AI model based on user input.

[0489] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0490] Step 1:

[0491] The user inputs information. Users access the user interface via a web browser or mobile application and input their experiences and future goals in text format. The entered data is then transmitted to the device as information related to the user's career development.

[0492] Step 2:

[0493] The device sends data. The device converts the text data entered by the user into JSON format and sends it to the server as an HTTP request. This process verifies the format of the input data to maintain data integrity.

[0494] Step 3:

[0495] The server receives the data. The server receives the HTTP request sent from the terminal and extracts the user's input data from the request body. The server verifies the integrity of the data and checks for any invalid data.

[0496] Step 4:

[0497] The server generates prompt text. The server analyzes the received user data and generates prompt text to input into the AI ​​model. This process uses natural language processing techniques to appropriately summarize the user's input and format it as prompt text.

[0498] Step 5:

[0499] The server sends a prompt message to the generating AI model. The server sends the generated prompt message to the generating AI model via the API. The generating AI model receives the prompt message as input and generates advice regarding the user's career development.

[0500] Step 6:

[0501] The server receives the response from the generated AI model. The server receives the response from the generated AI model and analyzes its contents. The response includes specific advice and recommendations to support the user's career development.

[0502] Step 7:

[0503] The terminal displays the results to the user. The terminal displays the advice received from the server on the user interface. The user can review the advice and recommendations on the screen and use them to help with their future career development.

[0504] (Application Example 1)

[0505] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0506] In modern society, it is difficult to efficiently provide appropriate information based on the individual user's experiences and future goals. In particular, there is a demand for personalized information delivery that meets the diverse needs of users, but this is difficult to achieve with conventional systems. Therefore, there is a need for a system that generates relevant information based on user input and delivers it appropriately.

[0507] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0508] In this invention, the server includes means for inputting the user's experiences and future goals, generation means for generating relevant information based on the relevant information, and distribution means for delivering the generated information to the user. This enables the generation and delivery of information tailored to the individual needs of the user.

[0509] "A means of inputting user experiences and future goals" refers to a function that provides an interface for users to input their past experiences and future goals in text format.

[0510] "Generating means for generating related information based on relevant information" refers to a function that processes information entered by the user to generate related content and data.

[0511] "A means of delivering generated information to users" refers to a function that provides generated content and data to users in an appropriate format.

[0512] A "generative AI model" is an artificial intelligence model used to generate relevant information based on user input.

[0513] A "prompt statement" is an instruction given to a generative AI model, used to determine the content and format of the information that will be generated.

[0514] To implement this invention, an application installed on the user's device is used. The user uses a device such as a smartphone or tablet to input their experiences and future goals in text format. The entered information is sent to a server and stored in a database.

[0515] The server generates relevant information using a generative AI model based on the stored information. This generative AI model can use, for example, OpenAI's GPT. The generated information is selected according to the user's interests and needs and delivered to the user's device in an appropriate format.

[0516] For example, if a user enters "I am interested in project management using AI technology," the server will generate content such as "the latest trends in project management using AI" and "success stories of AI project management" and deliver it to the user.

[0517] An example of a prompt message is: "User experience: Project management. Goal: Project management using AI technology. Generate relevant content."

[0518] In this way, it becomes possible to generate and deliver information tailored to the individual needs of users.

[0519] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0520] Step 1:

[0521] The user launches an application on their device and enters their experiences and future goals in text format. The entered information is sent from the device to the server. The input data consists of text information about the user's experiences and goals.

[0522] Step 2:

[0523] The server stores the received user input information in a database. During this process, the input data is converted to an appropriate format before being stored in the database. The database also records each user's experience and goals.

[0524] Step 3:

[0525] The server uses a generative AI model to generate relevant information based on stored user information. Specifically, it inputs prompt statements into the generative AI model and generates relevant content. The input is the prompt statement, and the output is the generated content.

[0526] Step 4:

[0527] The server sorts the generated content according to the user's interests and needs. The sorted information is filtered to be useful to the user. The input is the generated content, and the output is the sorted content.

[0528] Step 5:

[0529] The server delivers the selected content to the user's device. The user can view the delivered information on their device. The input is the selected content, and the output is the information displayed on the user's device.

[0530] (Example 2)

[0531] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0532] In modern organizations, quickly and accurately finding the right people for a project is crucial, but selecting the right individuals from a vast amount of data is difficult. Furthermore, efficiently scheduling meetings with selected individuals is also a challenge.

[0533] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0534] In this invention, the server includes means for inputting the user's experience and future goals into an information processing device, means for recommending appropriate individuals within the organization based on the relevant information, and means for automatically setting up meetings with the recommended individuals. This makes it possible to quickly recommend the most suitable personnel for a project and efficiently set up meetings.

[0535] An "information processing device" is a device that receives input from a user and processes the data.

[0536] A "user" is an entity that uses a system to input information and obtain results.

[0537] "Experience" is a general term for the knowledge and skills a user has acquired in the past.

[0538] "Future goals" refer to the future state or outcome that the user hopes to achieve.

[0539] An "organization" is a group of members who come together to achieve a specific purpose.

[0540] A "personnel recommendation system" is a method for selecting appropriate individuals within an organization based on the information entered.

[0541] "Deliverables" is a general term for the results obtained from past work or projects undertaken by the team members.

[0542] An "information recording device" is a device that can store data and retrieve it as needed.

[0543] A "meeting scheduling mechanism" is a means for automatically scheduling meetings with recommended individuals.

[0544] A "private meeting" is a meeting held one-on-one with a specific person.

[0545] As an embodiment of this invention, the following system is constructed.

[0546] The server functions as an information processing device, receiving input from users. Users input their experiences and future goals through a terminal. Based on this information, the server performs a personnel recommendation system to recommend suitable individuals within the organization. This process involves using AI algorithms to learn characteristics from the deliverables of members and registering them in an information recording device. Specifically, machine learning frameworks such as TensorFlow and PyTorch are used to analyze data and build models.

[0547] The terminal receives prompt messages from the user and sends them to the server. For example, a prompt message such as "Please recommend an employee who is proficient in AI technology" might be entered. Based on this prompt message, the server uses a pre-trained AI model to recommend the most suitable employee.

[0548] Furthermore, the server includes a meeting scheduling mechanism that automatically arranges meetings with recommended individuals. This allows users to efficiently find suitable personnel for their projects and quickly schedule necessary meetings. This system is expected to optimize talent utilization within organizations and improve project success rates.

[0549] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0550] Step 1:

[0551] Users input their experiences and future goals through their terminals. This information is sent to the server as foundational data to identify the skills and characteristics required for the project. The input information is transmitted to the server in text format.

[0552] Step 2:

[0553] The server uses the received user information to collect relevant data from the organization's member database. Specifically, it uses SQL queries to extract data on members' past projects and achievements. This data serves as input for analysis by AI algorithms.

[0554] Step 3:

[0555] The server preprocesses the collected data and converts it into a format usable by the AI ​​model. For example, it converts text data into numerical vectors and imputes missing values. This process uses data processing libraries such as Pandas and NumPy. The preprocessed data is then used as input for the AI ​​model.

[0556] Step 4:

[0557] The server runs an AI model using pre-processed data to identify members who meet the user's requirements. Specifically, it analyzes the data using a neural network model built with TensorFlow or PyTorch and recommends the most suitable individuals. This result is generated as a recommendation list.

[0558] Step 5:

[0559] The server sends the generated recommendation list to the terminal. The user reviews this list via the terminal and selects suitable personnel for the project. The recommendation list includes information such as the names, skills, and past achievements of the members.

[0560] Step 6:

[0561] The server automatically schedules meetings with individuals selected by the user. Specifically, it uses a calendar API to coordinate the schedules of the user and selected members and set up meetings. This allows users to efficiently schedule meetings and move projects forward.

[0562] (Application Example 2)

[0563] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0564] In modern organizations, quickly identifying the right people and assigning them to the right tasks is a critical challenge. However, traditional methods make it difficult to accurately understand the characteristics and skills of individual workers and select the most suitable individuals. Furthermore, it is difficult to monitor work progress in real time and reassign workers as needed. This can lead to decreased work efficiency and wasted resources.

[0565] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0566] In this invention, the server includes means for inputting the user's experience and future goals, means for recommending appropriate individuals within the organization based on the relevant information, means for automatically setting appointments with the recommended individuals, means for recommending the most suitable workers according to the work content, and means for analyzing the progress of work and the necessary skills in real time. This enables the optimal allocation of personnel within the organization, leading to improved work efficiency and effective use of resources.

[0567] "A means of inputting user experiences and future goals" refers to an interface for inputting data about individual users' past experiences and goals they wish to achieve in the future.

[0568] A "personnel recommendation system that recommends appropriate individuals within an organization based on relevant information" is an algorithm that analyzes the input information and selects and recommends the person within the organization who is most suitable for that information.

[0569] "An appointment scheduling method that automatically sets up appointments with recommended individuals" refers to a system that automatically adjusts and sets the date and time of meetings or interviews between recommended individuals and users.

[0570] "A means of recommending the most suitable worker according to the work content" refers to a function for selecting and recommending workers who possess the most suitable skills and experience for a particular task.

[0571] "Means for analyzing work progress and required skills in real time" refers to technologies for monitoring and analyzing the progress of work and the skills required for that work in real time.

[0572] To implement this invention, it is necessary to build a system in which a server plays a central role. The server provides an interface for users to input their experiences and future goals, and runs an AI algorithm to recommend suitable individuals within the organization based on the input information. Specifically, an AI model is built using a programming language such as Python, and a database management system (e.g., MySQL) is used to manage the characteristics and skill sets of individuals within the organization.

[0573] The server uses a calendar API and other tools to adjust schedules and automatically set appointments with recommended individuals. It also analyzes work progress and required skills in real time to recommend the most suitable worker for each task. This requires software to collect and analyze data from sensors mounted on robots within the factory.

[0574] As a concrete example, if the installation of a specific part is delayed in the assembly process of a certain product, the server will recommend a worker who is familiar with that process. An example of a prompt to the generating AI model might be: "The installation of part Y is delayed in the assembly process of product X. Please recommend the most suitable worker for installing part Y."

[0575] In this way, the server enables the optimal allocation of personnel within the organization, improving work efficiency and making effective use of resources.

[0576] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0577] Step 1:

[0578] The server provides an interface for users to input their experiences and future goals. Users enter past projects and goals they wish to achieve. The entered data is sent to the server and stored in the database.

[0579] Step 2:

[0580] The server executes an AI algorithm to recommend suitable individuals within the organization based on the input information. The server retrieves the characteristics and skill sets of individuals within the organization from a database and compares them with the input information using a generative AI model. This allows it to select the most suitable individuals and generate a recommendation list.

[0581] Step 3:

[0582] The server automatically schedules appointments with recommended individuals. Using a calendar API, the server coordinates the schedules of both the recommended person and the user to select a suitable date and time. The selected date and time are then notified to both the user and the recommended person.

[0583] Step 4:

[0584] The server analyzes the progress of a task and the required skills in real time to recommend the most suitable worker for that task. The server collects data from sensors mounted on robots within the factory to evaluate the progress of the task. It compares the required skills with the skill sets of the workers to select the most suitable worker.

[0585] Step 5:

[0586] The server generates prompts for the AI ​​model and recommends workers as needed. For example, it generates a prompt such as, "The installation of part Y is delayed in the assembly process of product X. Please recommend the most suitable worker for installing part Y," and inputs it into the AI ​​model. This then recommends the most suitable worker.

[0587] (Example 3)

[0588] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0589] Traditional appointment scheduling systems required users to manually adjust schedules, which was time-consuming and laborious. Furthermore, the process of finding the right person was cumbersome, hindering efficient communication.

[0590] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0591] In this invention, the server includes means for inputting user requests in natural language, means for analyzing user requests using a generative AI model, and means for recommending appropriate individuals based on the analysis results. This enables users to efficiently set appointments and communicate quickly with appropriate individuals.

[0592] "A means of inputting user requests in natural language" refers to a function that provides an interface for users to input their desired appointment date, time, and format in natural language.

[0593] "Methods for analyzing user requests using generative AI models" refers to a function that uses generative AI models to analyze natural language requests entered by users and to identify specific appointment dates, times, and formats.

[0594] "Means for recommending appropriate individuals based on analysis results" refers to a function that selects and recommends the most suitable person based on the analyzed user requirements.

[0595] "Means of obtaining schedules with recommended individuals" refers to the function of using schedule management software to obtain schedule information of recommended individuals.

[0596] "A means of finding a time that works for both the user and the recommended person" refers to a function that compares the schedules of the user and the recommended person to find available time for both of them.

[0597] The "automatic appointment scheduling based on available time" feature is a function that automatically schedules appointments based on the availability of both the user and the recommended person.

[0598] A description of embodiments for carrying out this invention will be given.

[0599] Users enter their appointment preferences in natural language using their device. For example, they can enter specific dates, times, and formats, such as "I'd like to schedule a one-on-one appointment for next Monday." This input is done through a means of entering the user's request in natural language.

[0600] The server receives input from the user and performs analysis using a generative AI model. This analysis utilizes natural language processing technology to convert the user's request into a specific appointment date, time, and format. A general-purpose natural language processing model can be used as the generative AI model. An example of a prompt is, "Please suggest the best appointment date and time based on the user's preferences."

[0601] Based on the analysis results, the server recommends a suitable person. To obtain the recommended person's schedule, the server uses scheduling software. Specifically, it uses common scheduling software such as the Google Calendar API to retrieve the schedule information of both the user and the recommended person.

[0602] Based on the acquired schedule information, the server finds a time that is convenient for both the user and the recommended person. To automatically set an appointment at the found time, the server again uses the schedule management software and adds the appointment to the calendar. This series of processes allows the user to set appointments efficiently. The flow of the specific process in Example 3 will be explained using Figure 15.

[0603] Step 1:

[0604] The user enters their appointment preferences in natural language using a terminal. For example, they might enter a specific date, time, and format, such as, "I'd like to schedule a one-on-one appointment for next Monday." This input forms the basis for the next processing step.

[0605] Step 2:

[0606] The server passes the natural language input received from the user to a generative AI model. The generative AI model uses prompts to analyze the user's request. Specifically, it analyzes the input natural language to identify the date, time, and format of the appointment. This analysis result becomes the input for the next step.

[0607] Step 3:

[0608] The server recommends a suitable person based on the analysis results. Information about the recommended person is retrieved from the database. The server searches the database using the analysis results and selects the most suitable person. This recommendation result becomes the input for the next step.

[0609] Step 4:

[0610] The server uses scheduling software to retrieve the schedules of recommended individuals. Specifically, it uses the Google Calendar API to obtain schedule information for both the user and the recommended individuals. This schedule information will then be used as input for the next step.

[0611] Step 5:

[0612] The server uses the retrieved schedule information to find a time that works for both the user and the recommended person. The server compares their availability and determines the optimal appointment date and time. This determined date and time becomes the input for the next step.

[0613] Step 6:

[0614] The server automatically sets appointments based on the time it finds. The server uses the Google Calendar API to add appointments to the calendar at the determined date and time. This eliminates the need for users to manually adjust their schedules.

[0615] (Application Example 3)

[0616] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0617] In modern organizations, efficiently scheduling appointments with the right person at the user's preferred date and time is crucial. However, traditional systems often require manual processes of checking the schedules of individuals within the organization based on the user's preferred date and time, and finding available time slots, which is time-consuming and laborious. Furthermore, the lack of functionality to automatically add confirmed appointments to the user's and the organization's personnel's calendars makes appointment management cumbersome.

[0618] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0619] In this invention, the server includes means for inputting the user's experience and future goals; means for recommending appropriate individuals within the organization based on the relevant information; means for automatically setting appointments with the recommended individuals; means for inputting the user's desired date and time, checking the schedules of individuals within the organization, and suggesting available times; and means for automatically adding confirmed appointments to the calendars of the user and individuals within the organization. This makes it possible to efficiently set appointments at the date and time desired by the user and to automate appointment management.

[0620] A "user" is an individual or member of an organization who intends to use the system to schedule an appointment.

[0621] "Experience" refers to the knowledge, skills, and achievements a user has acquired in the past, and is a factor considered when setting up an appointment.

[0622] "Future goals" refer to specific objectives or plans that the user wishes to achieve, and are factors considered when setting up an appointment.

[0623] A "person recommendation system" is a function that selects and recommends appropriate individuals within an organization based on their experience and future goals.

[0624] The "appointment setting method" is a function that automatically sets appointments with recommended individuals based on the user's preferred date and time.

[0625] A "schedule" is a timetable that shows the planned activities and free time of individuals within an organization.

[0626] "Free time" refers to periods within an organization when a person does not have other appointments or activities, and is the time available for scheduling appointments.

[0627] A "schedule" is a tool for recording and managing the schedules of users and individuals within an organization.

[0628] The system for carrying out this invention comprises a user terminal and a server. The user terminal is a device such as a smartphone or tablet, which provides an interface for the user to input their experiences and future goals. The server receives input from the user and performs a person recommendation means for recommending individuals within the organization.

[0629] The server retrieves the characteristics of individuals within the organization from a database based on the user's input and recommends the appropriate person. In this process, a generative AI model is used to select the person best suited to the user's experience and goals.

[0630] To schedule an appointment with a recommended person, the server uses an appointment scheduling mechanism. When the user enters their preferred date and time, the server checks the schedules of individuals within the organization and suggests available times. This allows the user to efficiently schedule appointments.

[0631] Confirmed appointments are automatically added to the calendars of both the user and individuals within the organization by the server. This simplifies appointment management and makes it easier for both users and individuals within the organization to check their schedules.

[0632] For example, if a user enters "I would like to schedule an appointment with the person in charge for 3 PM next Wednesday," the server will check the person in charge's schedule, and if it confirms that 3 PM is available, it will notify the user and confirm the appointment.

[0633] An example of a prompt message would be, "I would like to schedule an appointment with the person in charge for 3 PM next Wednesday. Please check their availability and confirm the reservation."

[0634] In this way, users can efficiently schedule appointments at their desired time and time, and communicate smoothly with people within their organization.

[0635] The flow of the specific processing in Application Example 3 will be explained using Figure 16.

[0636] Step 1:

[0637] The user uses a device to enter their experience, future goals, and preferred appointment dates and times. The entered data is then sent from the device to the server.

[0638] Step 2:

[0639] The server initiates a process to recommend individuals within the organization based on the user's experience and goals. Using a generative AI model, it analyzes the user's input data and retrieves the characteristics of suitable individuals from the database. This allows it to select the person best suited to the user.

[0640] Step 3:

[0641] The server checks the schedules of individuals within the organization based on the user's preferred date and time to set up an appointment with the recommended person. It uses a schedule management API to retrieve the person's availability and matches it with the user's preferred date and time.

[0642] Step 4:

[0643] The server suggests available time slots to the user when it finds them. Once the user accepts the suggested time, the server confirms the appointment and automatically adds it to the user's and other relevant individuals' calendars. This streamlines appointment management.

[0644] Step 5:

[0645] The server sends notifications to the user and relevant individuals within the organization regarding confirmed appointments. The notification system is used to send messages containing appointment details, allowing both parties to confirm their schedules.

[0646] In this way, users can efficiently schedule appointments at their desired dates and times, and communicate smoothly with people within their organization.

[0647] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0648] "Example of form 1"

[0649] One embodiment of the present invention involves a system that includes an emotion engine that recognizes the user's emotions as a means of inputting the user's experiences and future goals. This emotion engine analyzes emotions from the user's text or voice input and feeds the results back to the system. For example, if a user inputs, "I have experience in project management, and in the future I would like to work on project management utilizing AI technology," the emotion engine reads the user's motivation and expectations from that text.

[0650] "Example of form 2"

[0651] Furthermore, some systems recommend individuals by taking into account the user's emotions, as recognized by an emotion engine. In this system, the emotion engine analyzes the results to infer what kind of people the user wants to interact with, and then recommends individuals based on that. For example, if the user shows positive emotions, the system will recommend individuals who are also positive.

[0652] "Example of form 3"

[0653] Furthermore, some appointment scheduling systems take into account the user's emotions, as recognized by an emotion engine. This system considers the user's emotional state and schedules appointments at a time and format appropriate to that state. For example, if a user is feeling stressed, the system might schedule an appointment during a time when they can relax.

[0654] The following describes the processing flow for each example of the form.

[0655] "Example of form 1"

[0656] Step 1: The user enters their experiences and future goals into the system via text or voice input.

[0657] Step 2: The emotion engine analyzes the user's emotions from their input. This analysis utilizes natural language processing and speech analysis technologies.

[0658] Step 3: The emotion engine feeds the analysis results back into the system. This feedback includes the user's emotional state and its intensity.

[0659] "Example of form 2"

[0660] Step 1: The emotion engine analyzes the user's emotions.

[0661] Step 2: Based on the analysis results of the emotion engine, the system infers what kind of people the user wants to interact with.

[0662] Step 3: Based on the prediction results, the system recommends a suitable person to the user.

[0663] "Example of form 3"

[0664] Step 1: The emotion engine analyzes the user's emotions.

[0665] Step 2: Based on the analysis results of the emotion engine, the system determines the appropriate timing and format for the user's emotional state.

[0666] Step 3: The system sets an appointment based on its assessment results.

[0667] (Example 1)

[0668] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0669] Traditional systems could recommend the right person and schedule appointments based on the user's experience and goals, but they couldn't provide feedback that took the user's emotions into account. As a result, there was a lack of support that reflected the user's motivation and expectations.

[0670] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0671] In this invention, the server includes means for the user to input their experiences and future goals, means for recommending appropriate individuals within the group based on the relevant information, means for automatically setting appointments with the recommended individuals, means for analyzing the user's input information and recognizing their emotions, and means for providing feedback to the user based on the analysis results. This enables the provision of appropriate feedback that takes the user's emotions into consideration and supports the user in achieving their goals.

[0672] "A means for users to input experiences and future goals" refers to a device or software that provides an interface for users to input their past experiences and future goals in text format.

[0673] A "person recommendation system" is an algorithm or system that identifies and recommends appropriate individuals within a group based on information entered by the user.

[0674] An "appointment setting tool" is a device or software that has the function of automatically scheduling meetings or interviews with recommended individuals.

[0675] "Emotion analysis means" refers to a technology or system that analyzes user input information to recognize the user's emotions and motivations.

[0676] A "feedback tool" is a device or software that has the function of providing appropriate advice or information to the user based on the results of sentiment analysis.

[0677] This invention is a system that provides an interface for users to input their experiences and future goals. Users can input information in text format using a dedicated application on their terminal or a web browser. The input information is transmitted from the terminal to the server.

[0678] The server stores the received information in a database. This database can use a common relational database management system (RDBMS) such as MySQL or PostgreSQL. The stored information is analyzed by a person recommendation system to identify and recommend suitable individuals to the user.

[0679] Furthermore, the server uses sentiment analysis tools to analyze the user's emotions from their input information. This analysis utilizes a sentiment engine that leverages natural language processing (NLP) technology. Specifically, services such as Google Cloud Natural Language API and IBM Watson Natural Language Understanding can be used.

[0680] The analysis results are provided to the user through a feedback mechanism. This feedback is sent to the user's device as advice and support information to help them achieve their goals. The user can then review the feedback on their device and use it to guide their next actions.

[0681] For example, if a user enters "I have experience in project management and would like to work on project management using AI technology in the future," the sentiment analysis tool will read the user's motivation and expectations from that text, and the feedback tool will provide advice based on that.

[0682] An example of a prompt for a generative AI model is, "Analyze the user's input to understand their motivation and expectations, and generate feedback." By using this prompt, the AI ​​model can generate feedback that takes the user's emotions into account.

[0683] The flow of the specific processing in Example 1 will be explained using Figure 17.

[0684] Step 1:

[0685] Users access the user interface via a dedicated application or web browser using their device. Users enter their experiences and future goals into text boxes. Once they have finished entering the data, they click the "Submit" button, sending the data from their device to the server. The input data consists of text information about the user's experiences and goals.

[0686] Step 2:

[0687] The server receives user input data sent from the terminal. The received data is stored in the database. The server establishes a database connection and executes SQL queries to save the user input data. The input is the user's text information, and the output is the information stored in the database.

[0688] Step 3:

[0689] The server passes stored user input data to the sentiment analysis tool. The sentiment analysis tool uses natural language processing technology to analyze emotions from the text. The server sends an API request to the sentiment engine and receives the analysis results. The input is text information obtained from the database, and the output is the analysis result regarding the user's emotions.

[0690] Step 4:

[0691] The server provides feedback to the user using a feedback mechanism based on the analysis results obtained from the sentiment analysis mechanism. The server generates a feedback message based on the analysis results and sends it to the terminal. The user can view the feedback message on the terminal. The input is the result of the sentiment analysis, and the output is the feedback message provided to the user.

[0692] (Application Example 1)

[0693] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0694] In today's information society, it is crucial to recommend appropriate people and products based on users' experiences and future goals. However, conventional systems often fail to consider user emotions when making recommendations, making it difficult to meet user expectations.

[0695] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0696] In this invention, the server includes means for inputting the user's experiences and future goals, means for recommending appropriate individuals within the group organization based on the relevant information, means for automatically setting appointments with the recommended individuals, means for analyzing the user's input information and emotions, and means for recommending products based on the analysis results. This enables personalized recommendations that take the user's emotions into consideration.

[0697] "Means for inputting user experiences and future goals" refers to a feature that provides an interface for users to input their past experiences and future goals in text or voice.

[0698] "Person recommendation methods" are functions that identify and recommend appropriate individuals within a group organization based on user input information.

[0699] The "appointment scheduling method" is a function that automatically schedules meetings and interviews with recommended individuals.

[0700] "Emotion analysis tools" are functions that analyze user input information to evaluate the user's emotions and motivation.

[0701] A "product recommendation method" is a function that selects and recommends the most suitable product to the user based on the results of sentiment analysis.

[0702] The system for implementing this invention consists of a terminal equipped with an interface for inputting the user's experiences and future goals, and a server that analyzes the input information. The terminal is a device such as a smartphone or computer, and allows the user to input information in text or voice. The server uses software such as Python or TensorFlow to analyze the user's input information with a natural language processing library (such as NLTK) and perform sentiment analysis.

[0703] The server is equipped with a product recommendation engine that recommends the most suitable products to users based on the results of sentiment analysis. This engine selects relevant products while considering the user's purchasing intent and expectations. Furthermore, the server also has a function to recommend appropriate individuals within the group organization and automatically set up appointments based on the user's input information.

[0704] For example, if a user inputs "I've recently become interested in fitness and am looking for fitness-related gadgets" using their device, the server analyzes this information and determines that the user has a high level of interest. Based on this, it recommends fitness bands and smartwatches. Similarly, if a user inputs "I have experience in project management and would like to work on project management using AI technology in the future," the server recommends appropriate experts and sets up interview appointments.

[0705] An example of a prompt to input into the generative AI model is: "Analyze the user's input text and recommend products that will increase their purchase intent. Input: 'I've recently become interested in fitness and am looking for fitness-related gadgets.'"

[0706] The flow of a specific process in Application Example 1 will be explained using Figure 18.

[0707] Step 1:

[0708] Users input their experiences and future goals using text or voice via a device. The input data is sent from the device to the server. The input data includes information about the user's interests and goals.

[0709] Step 2:

[0710] The server analyzes the received input data using a natural language processing library (such as NLTK). The analysis extracts the user's intent and emotions. Specifically, this involves text tokenization, part-of-speech tagging, and the calculation of an emotion score.

[0711] Step 3:

[0712] The server uses a generative AI model to select the most suitable products for the user based on the results of sentiment analysis. It uses sentiment scores as input, and the product recommendation engine lists relevant products. The output is a list of products that match the user's interests.

[0713] Step 4:

[0714] The server recommends appropriate individuals within the group organization based on user input. Using the user's goals and experience as input, the person recommendation engine identifies suitable experts. The output is information about the recommended individuals.

[0715] Step 5:

[0716] The server automatically schedules appointments with recommended individuals. Using the recommended person's information and the user's preferred date and time as input, the scheduling algorithm determines the optimal date and time. The output is the details of the scheduled appointment.

[0717] (Example 2)

[0718] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0719] In modern organizations, it is crucial to recommend the right person quickly and accurately, but traditional systems struggle to adequately consider users' feelings and preferences when making recommendations. Furthermore, scheduling appointments with recommended individuals is often done manually, hindering efficient talent utilization.

[0720] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0721] In this invention, the server includes means for inputting user information, means for recommending appropriate individuals within the organization based on the relevant information, means for automatically setting appointments with the recommended individuals, means for analyzing the user's emotions, and means for recommending individuals based on the analysis results. This enables the recommendation of appropriate personnel that takes into account the user's emotions and wishes, and efficient appointment setting.

[0722] "Means for inputting user information" refers to an interface that allows users to input their own information and desired conditions into the system.

[0723] A "person recommendation system" refers to an algorithm or process that identifies and recommends suitable individuals within an organization based on the information entered.

[0724] The "appointment scheduling method" is a function that automatically schedules meetings and interviews with recommended individuals.

[0725] "Methods for analyzing user emotions" refer to analytical techniques that identify a user's emotional state based on their input data.

[0726] "A method for recommending individuals based on analysis results" refers to a process for recommending the most suitable individuals by taking into account the results of the user's sentiment analysis.

[0727] "Methods for learning individual characteristics from the deliverables of members" refers to techniques for learning the characteristics and skills of individuals by analyzing the deliverables of tasks and projects that members of an organization have performed in the past.

[0728] An "information recording device" is a database or storage system used to save the characteristics and skills of a person that have been learned.

[0729] An "individual interview" is a form of interview or meeting conducted one-on-one between the user and the recommended person.

[0730] A description of embodiments for carrying out this invention will be given.

[0731] The server provides an interface for users to input their information. Through this interface, users can enter their information and preferences. The entered information is stored in a database on the server.

[0732] The server uses an AI algorithm as a means of recommending individuals. This algorithm analyzes the output of its members using machine learning frameworks such as TensorFlow and PyTorch, and learns the characteristics of each individual. The learned characteristics are registered in an information recording device.

[0733] The device uses Affectiva or Microsoft Azure sentiment analysis APIs to analyze the user's emotions. Based on text and voice data entered by the user, it identifies the user's current emotional state. This analysis result is then sent to the server.

[0734] The server then performs a recommendation process based on the analysis results. This allows it to identify and recommend the person who best matches the user's preferences and emotional state.

[0735] Furthermore, the server automatically schedules interviews and meetings with recommended individuals using an appointment scheduling mechanism. This process allows users to efficiently connect with suitable personnel.

[0736] As a concrete example, if a user enters the prompt "Please recommend the best employee for the AI ​​project. I am motivated," the server will use an AI algorithm to analyze employee data and list motivated AI engineers. This list will be displayed on the user's device, and the user can select the most suitable employee from among them.

[0737] The flow of the specific processing in Example 2 will be explained using Figure 19.

[0738] Step 1:

[0739] Users input their information and preferences through the system interface. This information is sent to the server and stored in a database. This includes project type and required skill set.

[0740] Step 2:

[0741] The server collects data from a database regarding the past projects and achievements of members within the organization. Based on the collected data, an AI algorithm using TensorFlow or PyTorch learns the characteristics of each member. Through this process, the skills and characteristics of each member are registered in the information recording device.

[0742] Step 3:

[0743] The device uses Affectiva or Microsoft Azure sentiment analysis APIs to analyze the user's emotions. Based on text and voice data entered by the user, it identifies the current emotional state. The analysis results are sent to the server as data indicating the user's emotional state.

[0744] Step 4:

[0745] The server executes an AI algorithm based on the user's preferences and sentiment analysis results. This identifies the most suitable members for the user's criteria and generates a recommendation list. The recommendation list takes into account the user's preferences and emotional state.

[0746] Step 5:

[0747] The server presents the generated recommendation list to the user. The user can then select project members based on this list. Specifically, the list displays the member's name, skill set, and past achievements.

[0748] Step 6:

[0749] The server automatically schedules appointments with selected members. Using the appointment scheduling mechanism, it efficiently coordinates interview and meeting schedules and notifies the user. This allows the user to quickly connect with the appropriate personnel.

[0750] (Application Example 2)

[0751] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0752] In modern manufacturing environments, proper personnel allocation and team formation are crucial for improving production efficiency. However, traditional methods have made it difficult to recommend personnel that fully consider the characteristics and emotional states of workers, thus hindering the creation of optimal teams. This has resulted in challenges such as decreased production efficiency and reduced worker motivation.

[0753] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0754] In this invention, the server includes means for inputting the user's experience and future goals, means for recommending appropriate individuals within the organization based on the relevant information, means for automatically setting appointments with the recommended individuals, means for learning the characteristics of workers and registering them in a database, and means for considering the user's emotional state using emotion analysis means and recommending the most suitable person. This enables optimal personnel placement and team formation that takes into account the characteristics and emotional state of workers.

[0755] "A means of inputting user experiences and future goals" refers to an interface that allows users to input their past experiences and future goals into the system.

[0756] A "person recommendation system" is a function that includes an algorithm for selecting and recommending appropriate individuals within an organization based on the information entered.

[0757] The "appointment scheduling method" is a function that automatically adjusts and sets the date and time for meetings or interviews with recommended individuals.

[0758] "Methods for learning worker characteristics and registering them in a database" refers to the process by which AI analyzes workers' past performance and skills and saves the results in a database.

[0759] "Emotional analysis means" refers to technology that analyzes a user's current emotional state and reflects the results in person recommendations.

[0760] The system for carrying out this invention includes a server, a user terminal, and a database. The server provides an interface for users to input their experiences and future goals, and recommends appropriate individuals within the organization based on the input information. The server uses an AI algorithm to learn the characteristics of workers and registers them in the database. Furthermore, it uses sentiment analysis means to analyze the user's emotional state and reflects the results in person recommendations.

[0761] The server implements AI algorithms using Python and utilizes the OpenAI API for sentiment analysis. The database stores data on workers' skills, past performance, and emotional states. The user terminal receives recommendation results from the server and automatically sets up appointments with the recommended individuals.

[0762] As a concrete example, when setting up a new production line in a factory, the server identifies workers who have performed well in past projects, confirms that their current emotional state is motivated, and recommends them as leaders. An example of a prompt to input into the generative AI model would be, "Recommend the best worker to set up the new production line. Please consider past performance and current emotional state."

[0763] The flow of a specific process in Application Example 2 will be explained using Figure 20.

[0764] Step 1:

[0765] The user uses a terminal to input their experiences and future goals. The entered information is sent to the server. The server receives this information and stores it in a database.

[0766] Step 2:

[0767] The server uses an AI algorithm to recommend suitable individuals within the organization based on user information stored in the database. The AI ​​algorithm analyzes the worker's past performance and skills to select the person best suited to the user's goals. The output of this process is a list of recommended individuals.

[0768] Step 3:

[0769] The server analyzes the user's emotional state using emotion analysis tools. Based on the user's input information and past data, it infers their current emotional state. The analysis results are reflected in the person recommendation. Specifically, users who show motivated emotions will be recommended similarly motivated individuals.

[0770] Step 4:

[0771] The server automatically sets up appointments with recommended individuals. It selects the optimal date and time, taking into account the user's schedule and preferences. The scheduled appointment information is sent to the user's terminal, and the user is notified.

[0772] Step 5:

[0773] Users can view recommendation results and appointment information through their terminal. They can change or cancel appointments as needed. The server updates the database in response to user actions and sends notifications to relevant individuals.

[0774] (Example 3)

[0775] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0776] Traditional systems may increase the user's psychological burden by scheduling appointments without considering their emotional state. Furthermore, they may not adequately reflect the user's experience and goals when recommending appropriate individuals. This presents a challenge in providing users with optimal communication opportunities.

[0777] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0778] In this invention, the server includes means for inputting the user's experiences and future goals, means for recommending appropriate individuals within the organization based on the relevant information, means for automatically setting appointments with the recommended individuals, means for analyzing the user's emotional state, and means for determining the optimal appointment time based on the emotional state. This makes it possible to provide optimal communication opportunities that take the user's emotional state into consideration.

[0779] "A means of inputting user experiences and future goals" refers to a function that provides an interface for users to input their past experiences and future goals into the system.

[0780] "Personnel recommendation methods" refer to algorithms and processes that select and recommend appropriate individuals within an organization based on user input information.

[0781] The "scheduling method" is a function that automatically coordinates and sets schedules with recommended individuals.

[0782] "Emotional analysis methods" are technologies that analyze a user's input data and past behavior to infer their current emotional state.

[0783] "Methods for determining the optimal appointment time based on emotional state" refers to a process that takes into account the user's emotional state and selects the optimal time to reduce psychological burden.

[0784] As an embodiment of this invention, the following system is constructed.

[0785] Users input their experiences and future goals through a terminal. This allows the system to understand the user's needs and desires. The entered information is sent to a server and stored in a database.

[0786] The server recommends suitable individuals within the organization based on information received from the user. As a means of recommending individuals, the server utilizes characteristic information of members registered in a database. This makes it possible to select the person best suited to the user's needs.

[0787] Next, the server uses scheduling software such as the Google Calendar API to automatically schedule appointments with recommended individuals. When a user enters a prompt such as, "I'd like to schedule a 1-on-1 appointment for next Monday," the server compares the user's and the recommended individuals' schedules, finds a common time slot, and schedules the appointment.

[0788] Furthermore, the server uses a generative AI model to analyze the user's emotional state. This emotional analysis tool analyzes the user's input data and past behavior to infer their current emotional state. For example, if the server determines that the user is experiencing stress, it uses this information to select the optimal time to alleviate their psychological burden and schedule activities accordingly.

[0789] In this way, users can obtain the optimal communication opportunity that takes their own emotional state into consideration. The flow of the specific processing in Example 3 will be explained using Figure 21.

[0790] Step 1:

[0791] Users input their experiences and future goals through their terminal. The entered information is sent to the server as prompt messages. For example, specific requests such as "I would like to schedule a one-on-one appointment for next Monday" might be entered. This input data is used as foundational data to understand the user's needs.

[0792] Step 2:

[0793] The server analyzes the prompt received from the user and recommends the appropriate person within the organization. The server accesses a database and, based on member characteristics, selects the person best suited to the user's needs. This process analyzes the user's input data and generates a list of recommended individuals.

[0794] Step 3:

[0795] The server uses the Google Calendar API to retrieve the schedules of the user and the recommended person. The server compares the schedules of both parties to find common free time. In this step, the schedule data is analyzed to determine the best time for the appointment.

[0796] Step 4:

[0797] The server uses a generative AI model to analyze the user's emotional state. Based on the user's input data and past behavior, the emotion analysis tool infers the user's current emotions. For example, if it determines that the user is feeling stressed, this information is taken into consideration in the next step.

[0798] Step 5:

[0799] The server determines the optimal appointment time based on the user's emotional state. To reduce psychological burden, it selects a time when the user can relax. This step takes into account the results of the emotional analysis to select the optimal time.

[0800] Step 6:

[0801] The server notifies the user and the recommended person of the details of the confirmed appointment. The notification is sent via email or calendar reminder. This allows the user and the recommended person to check the appointment details and have an opportunity to communicate.

[0802] (Application Example 3)

[0803] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0804] In today's business environment, communication that takes into account the user's emotional state is essential. However, traditional appointment scheduling systems fail to consider user emotions, making it difficult to schedule appointments at the optimal time. This can lead to decreased user satisfaction and hinder efficient communication.

[0805] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0806] In this invention, the server includes means for inputting the user's experience and future goals, means for recommending appropriate individuals within the organization based on the relevant information, means for automatically setting appointments with the recommended individuals, and means for recognizing the user's emotional state and adjusting the timing of appointments based on that emotional state. This makes it possible to set appointments at the optimal timing according to the user's emotional state, thereby improving user satisfaction.

[0807] A "user" is an individual or group that uses the system to schedule an appointment.

[0808] "Experience" is a general term for the knowledge, skills, and experiences a user has acquired in the past.

[0809] "Future goals" refer to the future plans and objectives that the user hopes to achieve.

[0810] "Means of input" refers to the methods or devices that users use to provide information to a system.

[0811] "Within the organization" refers to the internal workings of a specific company or group.

[0812] The "right person" is the individual who best matches the user's requirements and conditions.

[0813] A "recommendation method for recommending individuals" refers to a method or device for selecting and suggesting the most suitable person based on user information.

[0814] An "appointment" is a reservation for a meeting or conference at a specific date and time.

[0815] An "automatic appointment scheduling method" refers to a method or device for a system to automatically determine appointments based on user conditions.

[0816] "Emotional state" refers to the user's psychological state or mood.

[0817] "Emotion recognition means for recognizing and adjusting appointment timing based on the emotional state" refers to a method or device for analyzing a user's emotions and determining the optimal appointment time based on the results.

[0818] The system for carrying out this invention includes a terminal for inputting the user's experience and future goals, a server for recommending appropriate individuals within the organization, and a server for automatically scheduling appointments with the recommended individuals. Furthermore, it includes emotion recognition means for recognizing the user's emotional state and adjusting the timing of appointments based on that emotional state.

[0819] The server receives information entered by the user through the terminal and analyzes the user's emotional state using a generative AI model. During this process, it uses an emotion recognition API (e.g., Microsoft Azure Emotion API) to identify the user's emotions. Next, the server uses scheduling software (e.g., Google Calendar API) to retrieve the availability of appropriate individuals within the organization.

[0820] The server calculates the optimal appointment timing based on the user's emotional state and sets the appointment accordingly. This process allows for appointment scheduling at a time that suits the user's emotional state, thereby improving user satisfaction.

[0821] For example, if a user enters "I'd like to discuss security next Monday" into their device, the server uses an emotion recognition API to analyze the user's stress level. If the server determines that the stress level is high, it checks the availability of a support staff member and schedules an appointment for a more relaxed afternoon time.

[0822] An example of a prompt message would be, "If the user is feeling stressed, please tell me how to schedule an appointment during a time when they can relax."

[0823] The flow of the specific processing in Application Example 3 will be explained using Figure 22.

[0824] Step 1:

[0825] The user enters their experience, future goals, and desired appointment date and time via a terminal. The entered data is sent to the server. The server receives this data and prepares to analyze the user's request.

[0826] Step 2:

[0827] The server uses an emotion recognition API to analyze the user's emotional state. The input includes user voice and text data. The API processes this data and outputs the user's emotional state (e.g., stress level). Based on this output, the server understands the user's current emotional state.

[0828] Step 3:

[0829] The server runs a person recommendation algorithm that considers the user's input data and emotional state to recommend the right person within the organization. The inputs used are the user's experience, goals, and emotional state. The algorithm processes this data and outputs the most suitable person. Based on this output, the server identifies the recommended person.

[0830] Step 4:

[0831] The server uses scheduling software to retrieve the availability of the recommended person. The input includes the recommended person's ID and schedule information. The software processes this data and outputs their availability. Based on this output, the server identifies potential appointment times.

[0832] Step 5:

[0833] The server calculates the optimal appointment timing based on the user's emotional state. The inputs used are the user's emotional state and the availability of the recommended person. The server processes this data and outputs the optimal appointment time. Based on this output, the server automatically schedules the appointment.

[0834] Step 6:

[0835] The server notifies the user and the recommended person of the details of the scheduled appointment. The inputs used are the date, time, location, and participant information of the appointment. The server processes this data and outputs a notification message. The user and the recommended person receive this notification and confirm the appointment details.

[0836] (Other examples)

[0837] Since this is the same as the specific processing described in the other embodiments of the first embodiment above, the explanation will be omitted.

[0838] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0839] The data generation model 58 is a form of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0840] Other examples of generative AI include Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are some examples.

[0841] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0842] [Third Embodiment]

[0843] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0844] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0845] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0846] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0847] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0848] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0849] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0850] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0851] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0852] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0853] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0854] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[0855] "Example of form 1"

[0856] The system of the present invention provides a means for users to input their own experiences and future goals. Specifically, it allows users to input their experiences and goals in text format through a user interface. For example, if a user inputs "I have experience in project management and in the future I would like to work on project management utilizing AI technology," this information is stored in the system.

[0857] "Example of form 2"

[0858] Next, the personnel recommendation system recommends appropriate individuals within the group companies based on the input information. Specifically, it uses an AI algorithm to learn the characteristics of employees from their output and registers them in a database. For example, the AI ​​learns from an employee's past projects and achievements that the employee is proficient in AI technology and recommends that employee.

[0859] "Example of form 3"

[0860] Finally, the appointment scheduling method automatically sets up appointments with recommended individuals. Specifically, it sets up appointments such as one-on-one meetings according to the user's preferences. For example, if a user enters, "I would like to schedule a one-on-one appointment for next Monday," the system compares the schedules of the recommended individuals with the user's, finds a time that works for both parties, and sets up the appointment.

[0861] The following describes the processing flow for each example of the form.

[0862] "Example of form 1"

[0863] Step 1: The user enters their experience and future goals in text format through the system's user interface. For example, they might enter, "I have experience in project management, and in the future I would like to work on project management utilizing AI technology." Step 2: The entered information is saved in the system.

[0864] "Example of form 2"

[0865] Step 1: The personnel recommendation system uses an AI algorithm based on stored information to learn about individual characteristics from employee output.

[0866] Step 2: The learned characteristics are registered in the database.

[0867] Step 3: The AI ​​learns from an employee's past projects and achievements whether that employee is proficient in AI technology and recommends that employee.

[0868] "Example of form 3"

[0869] Step 1: The user enters "I would like to schedule a 1-on-1 appointment for next Monday."

[0870] Step 2: The appointment scheduling system compares the schedules of the recommended individuals with those of the user.

[0871] Step 3: Find a time that works for both parties and set up an appointment.

[0872] (Example 1)

[0873] Next, we will describe Embodiment 1 of Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0874] Conventional systems struggled to provide appropriate advice based on users' experiences and goals, and in particular, they were unable to effectively utilize the generation of prompts and responses using generative AI models. As a result, they lacked sufficient concrete information to support users' career development.

[0875] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0876] In this invention, the server includes means for inputting the user's experiences and future goals, means for generating prompt sentences to be input to a generative AI model based on the relevant information, and means for sending the generated prompt sentences to the generative AI model and receiving a response. This makes it possible to utilize the generative AI model based on the user's input and provide the user with appropriate advice.

[0877] "A means of inputting user experiences and future goals" refers to a function that provides an interface for users to input their past experiences and future goals in text format.

[0878] "Means for generating prompt text to input into a generative AI model" refers to a function that analyzes user input data and creates prompt text to provide information to the generative AI model in the most optimal format.

[0879] "Means for sending generated prompt sentences to a generation AI model and receiving responses" refers to a communication function for sending generated prompt sentences to a generation AI model and receiving its responses.

[0880] "A means of providing appropriate advice to users" refers to a function that presents users with specific advice to support their career development, based on responses received from a generative AI model.

[0881] This invention is a system in which a user inputs their own experiences and future goals, and then utilizes a generated AI model to provide appropriate advice based on that input. The following describes a specific form for implementing this system.

[0882] Users access the user interface through a web browser or mobile application. This interface provides a means for users to input their experiences and goals in text format. For example, a user might input, "I have experience in project management, and in the future I would like to work on project management utilizing AI technology."

[0883] The terminal sends the data entered by the user to the server. Typically, this data is packaged in JSON format and sent as an HTTP request. The server parses the received data and generates prompts for input into the AI ​​model based on the user's input. Programming languages ​​such as Python and Java are used for this process.

[0884] The generated prompt is sent to the AI ​​model. The server accesses the AI ​​model via an API and provides the prompt as input. For example, it can generate a prompt such as, "The user has project management experience and is interested in projects utilizing AI technology. What skills should they learn?"

[0885] Upon receiving a response from the generated AI model, the server provides appropriate advice to the user based on that information. This advice includes specific information to support the user's career development. The terminal displays the information received from the server in the user interface, allowing the user to view the advice and recommendations on the screen.

[0886] This system aims to provide users with specific and useful advice by utilizing a generated AI model based on user input.

[0887] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0888] Step 1:

[0889] The user inputs information. Users access the user interface via a web browser or mobile application and input their experiences and future goals in text format. The entered data is then transmitted to the device as information related to the user's career development.

[0890] Step 2:

[0891] The device sends data. The device converts the text data entered by the user into JSON format and sends it to the server as an HTTP request. This process verifies the format of the input data to maintain data integrity.

[0892] Step 3:

[0893] The server receives the data. The server receives the HTTP request sent from the terminal and extracts the user's input data from the request body. The server verifies the integrity of the data and checks for any invalid data.

[0894] Step 4:

[0895] The server generates prompt text. The server analyzes the received user data and generates prompt text to input into the AI ​​model. This process uses natural language processing techniques to appropriately summarize the user's input and format it as prompt text.

[0896] Step 5:

[0897] The server sends a prompt message to the generating AI model. The server sends the generated prompt message to the generating AI model via the API. The generating AI model receives the prompt message as input and generates advice regarding the user's career development.

[0898] Step 6:

[0899] The server receives the response from the generated AI model. The server receives the response from the generated AI model and analyzes its contents. The response includes specific advice and recommendations to support the user's career development.

[0900] Step 7:

[0901] The terminal displays the results to the user. The terminal displays the advice received from the server on the user interface. The user can review the advice and recommendations on the screen and use them to help with their future career development.

[0902] (Application Example 1)

[0903] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0904] In modern society, it is difficult to efficiently provide appropriate information based on the individual user's experiences and future goals. In particular, there is a demand for personalized information delivery that meets the diverse needs of users, but this is difficult to achieve with conventional systems. Therefore, there is a need for a system that generates relevant information based on user input and delivers it appropriately.

[0905] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0906] In this invention, the server includes means for inputting the user's experiences and future goals, generation means for generating relevant information based on the relevant information, and distribution means for delivering the generated information to the user. This enables the generation and delivery of information tailored to the individual needs of the user.

[0907] "A means of inputting user experiences and future goals" refers to a function that provides an interface for users to input their past experiences and future goals in text format.

[0908] "Generating means for generating related information based on relevant information" refers to a function that processes information entered by the user to generate related content and data.

[0909] "A means of delivering generated information to users" refers to a function that provides generated content and data to users in an appropriate format.

[0910] A "generative AI model" is an artificial intelligence model used to generate relevant information based on user input.

[0911] A "prompt statement" is an instruction given to a generative AI model, used to determine the content and format of the information that will be generated.

[0912] To implement this invention, an application installed on the user's device is used. The user uses a device such as a smartphone or tablet to input their experiences and future goals in text format. The entered information is sent to a server and stored in a database.

[0913] The server generates relevant information using a generative AI model based on the stored information. This generative AI model can use, for example, OpenAI's GPT. The generated information is selected according to the user's interests and needs and delivered to the user's device in an appropriate format.

[0914] For example, if a user enters "I am interested in project management using AI technology," the server will generate content such as "the latest trends in project management using AI" and "success stories of AI project management" and deliver it to the user.

[0915] An example of a prompt message is: "User experience: Project management. Goal: Project management using AI technology. Generate relevant content."

[0916] In this way, it becomes possible to generate and deliver information tailored to the individual needs of users.

[0917] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0918] Step 1:

[0919] The user launches an application on their device and enters their experiences and future goals in text format. The entered information is sent from the device to the server. The input data consists of text information about the user's experiences and goals.

[0920] Step 2:

[0921] The server stores the received user input information in a database. During this process, the input data is converted to an appropriate format before being stored in the database. The database also records each user's experience and goals.

[0922] Step 3:

[0923] The server uses a generative AI model to generate relevant information based on stored user information. Specifically, it inputs prompt statements into the generative AI model and generates relevant content. The input is the prompt statement, and the output is the generated content.

[0924] Step 4:

[0925] The server sorts the generated content according to the user's interests and needs. The sorted information is filtered to be useful to the user. The input is the generated content, and the output is the sorted content.

[0926] Step 5:

[0927] The server delivers the selected content to the user's device. The user can view the delivered information on their device. The input is the selected content, and the output is the information displayed on the user's device.

[0928] (Example 2)

[0929] Next, we will describe Example 2 of the Form Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0930] In modern organizations, quickly and accurately finding the right people for a project is crucial, but selecting the right individuals from a vast amount of data is difficult. Furthermore, efficiently scheduling meetings with selected individuals is also a challenge.

[0931] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0932] In this invention, the server includes means for inputting the user's experience and future goals into an information processing device, means for recommending appropriate individuals within the organization based on the relevant information, and means for automatically setting up meetings with the recommended individuals. This makes it possible to quickly recommend the most suitable personnel for a project and efficiently set up meetings.

[0933] An "information processing device" is a device that receives input from a user and processes the data.

[0934] A "user" is an entity that uses a system to input information and obtain results.

[0935] "Experience" is a general term for the knowledge and skills a user has acquired in the past.

[0936] "Future goals" refer to the future state or outcome that the user hopes to achieve.

[0937] An "organization" is a group of members who come together to achieve a specific purpose.

[0938] A "personnel recommendation system" is a method for selecting appropriate individuals within an organization based on the information entered.

[0939] "Deliverables" is a general term for the results obtained from past work or projects undertaken by the team members.

[0940] An "information recording device" is a device that can store data and retrieve it as needed.

[0941] A "meeting scheduling mechanism" is a means for automatically scheduling meetings with recommended individuals.

[0942] A "private meeting" is a meeting held one-on-one with a specific person.

[0943] As an embodiment of this invention, the following system is constructed.

[0944] The server functions as an information processing device, receiving input from users. Users input their experiences and future goals through a terminal. Based on this information, the server performs a personnel recommendation system to recommend suitable individuals within the organization. This process involves using AI algorithms to learn characteristics from the deliverables of members and registering them in an information recording device. Specifically, machine learning frameworks such as TensorFlow and PyTorch are used to analyze data and build models.

[0945] The terminal receives prompt messages from the user and sends them to the server. For example, a prompt message such as "Please recommend an employee who is proficient in AI technology" might be entered. Based on this prompt message, the server uses a pre-trained AI model to recommend the most suitable employee.

[0946] Furthermore, the server includes a meeting scheduling mechanism that automatically arranges meetings with recommended individuals. This allows users to efficiently find suitable personnel for their projects and quickly schedule necessary meetings. This system is expected to optimize talent utilization within organizations and improve project success rates.

[0947] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0948] Step 1:

[0949] Users input their experiences and future goals through their terminals. This information is sent to the server as foundational data to identify the skills and characteristics required for the project. The input information is transmitted to the server in text format.

[0950] Step 2:

[0951] The server uses the received user information to collect relevant data from the organization's member database. Specifically, it uses SQL queries to extract data on members' past projects and achievements. This data serves as input for analysis by AI algorithms.

[0952] Step 3:

[0953] The server preprocesses the collected data and converts it into a format usable by the AI ​​model. For example, it converts text data into numerical vectors and imputes missing values. This process uses data processing libraries such as Pandas and NumPy. The preprocessed data is then used as input for the AI ​​model.

[0954] Step 4:

[0955] The server runs an AI model using pre-processed data to identify members who meet the user's requirements. Specifically, it analyzes the data using a neural network model built with TensorFlow or PyTorch and recommends the most suitable individuals. This result is generated as a recommendation list.

[0956] Step 5:

[0957] The server sends the generated recommendation list to the terminal. The user reviews this list via the terminal and selects suitable personnel for the project. The recommendation list includes information such as the names, skills, and past achievements of the members.

[0958] Step 6:

[0959] The server automatically schedules meetings with individuals selected by the user. Specifically, it uses a calendar API to coordinate the schedules of the user and selected members and set up meetings. This allows users to efficiently schedule meetings and move projects forward.

[0960] (Application Example 2)

[0961] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as a "server," and the headset-type terminal 314 will be referred to as a "terminal."

[0962] In modern organizations, quickly identifying the right people and assigning them to the right tasks is a critical challenge. However, traditional methods make it difficult to accurately understand the characteristics and skills of individual workers and select the most suitable individuals. Furthermore, it is difficult to monitor work progress in real time and reassign workers as needed. This can lead to decreased work efficiency and wasted resources.

[0963] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0964] In this invention, the server includes means for inputting the user's experience and future goals, means for recommending appropriate individuals within the organization based on the relevant information, means for automatically setting appointments with the recommended individuals, means for recommending the most suitable workers according to the work content, and means for analyzing the progress of work and the necessary skills in real time. This enables the optimal allocation of personnel within the organization, leading to improved work efficiency and effective use of resources.

[0965] "A means of inputting user experiences and future goals" refers to an interface for inputting data about individual users' past experiences and goals they wish to achieve in the future.

[0966] A "personnel recommendation system that recommends appropriate individuals within an organization based on relevant information" is an algorithm that analyzes the input information and selects and recommends the person within the organization who is most suitable for that information.

[0967] "An appointment scheduling method that automatically sets up appointments with recommended individuals" refers to a system that automatically adjusts and sets the date and time of meetings or interviews between recommended individuals and users.

[0968] "A means of recommending the most suitable worker according to the work content" refers to a function for selecting and recommending workers who possess the most suitable skills and experience for a particular task.

[0969] "Means for analyzing work progress and required skills in real time" refers to technologies for monitoring and analyzing the progress of work and the skills required for that work in real time.

[0970] To implement this invention, it is necessary to build a system in which a server plays a central role. The server provides an interface for users to input their experiences and future goals, and runs an AI algorithm to recommend suitable individuals within the organization based on the input information. Specifically, an AI model is built using a programming language such as Python, and a database management system (e.g., MySQL) is used to manage the characteristics and skill sets of individuals within the organization.

[0971] The server uses a calendar API and other tools to adjust schedules and automatically set appointments with recommended individuals. It also analyzes work progress and required skills in real time to recommend the most suitable worker for each task. This requires software to collect and analyze data from sensors mounted on robots within the factory.

[0972] As a concrete example, if the installation of a specific part is delayed in the assembly process of a certain product, the server will recommend a worker who is familiar with that process. An example of a prompt to the generating AI model might be: "The installation of part Y is delayed in the assembly process of product X. Please recommend the most suitable worker for installing part Y."

[0973] In this way, the server enables the optimal allocation of personnel within the organization, improving work efficiency and making effective use of resources.

[0974] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0975] Step 1:

[0976] The server provides an interface for users to input their experiences and future goals. Users enter past projects and goals they wish to achieve. The entered data is sent to the server and stored in the database.

[0977] Step 2:

[0978] The server executes an AI algorithm to recommend suitable individuals within the organization based on the input information. The server retrieves the characteristics and skill sets of individuals within the organization from a database and compares them with the input information using a generative AI model. This allows it to select the most suitable individuals and generate a recommendation list.

[0979] Step 3:

[0980] The server automatically schedules appointments with recommended individuals. Using a calendar API, the server coordinates the schedules of both the recommended person and the user to select a suitable date and time. The selected date and time are then notified to both the user and the recommended person.

[0981] Step 4:

[0982] The server analyzes the progress of a task and the required skills in real time to recommend the most suitable worker for that task. The server collects data from sensors mounted on robots within the factory to evaluate the progress of the task. It compares the required skills with the skill sets of the workers to select the most suitable worker.

[0983] Step 5:

[0984] The server generates prompts for the AI ​​model and recommends workers as needed. For example, it generates a prompt such as, "The installation of part Y is delayed in the assembly process of product X. Please recommend the most suitable worker for installing part Y," and inputs it into the AI ​​model. This then recommends the most suitable worker.

[0985] (Example 3)

[0986] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0987] Traditional appointment scheduling systems required users to manually adjust schedules, which was time-consuming and laborious. Furthermore, the process of finding the right person was cumbersome, hindering efficient communication.

[0988] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0989] In this invention, the server includes means for inputting user requests in natural language, means for analyzing user requests using a generative AI model, and means for recommending appropriate individuals based on the analysis results. This enables users to efficiently set appointments and communicate quickly with appropriate individuals.

[0990] "A means of inputting user requests in natural language" refers to a function that provides an interface for users to input their desired appointment date, time, and format in natural language.

[0991] "Methods for analyzing user requests using generative AI models" refers to a function that uses generative AI models to analyze natural language requests entered by users and to identify specific appointment dates, times, and formats.

[0992] "Means for recommending appropriate individuals based on analysis results" refers to a function that selects and recommends the most suitable person based on the analyzed user requirements.

[0993] "Means of obtaining schedules with recommended individuals" refers to the function of using schedule management software to obtain schedule information of recommended individuals.

[0994] "A means of finding a time that works for both the user and the recommended person" refers to a function that compares the schedules of the user and the recommended person to find available time for both of them.

[0995] The "automatic appointment scheduling based on available time" feature is a function that automatically schedules appointments based on the availability of both the user and the recommended person.

[0996] A description of embodiments for carrying out this invention will be given.

[0997] Users enter their appointment preferences in natural language using their device. For example, they can enter specific dates, times, and formats, such as "I'd like to schedule a one-on-one appointment for next Monday." This input is done through a means of entering the user's request in natural language.

[0998] The server receives input from the user and performs analysis using a generative AI model. This analysis utilizes natural language processing technology to convert the user's request into a specific appointment date, time, and format. A general-purpose natural language processing model can be used as the generative AI model. An example of a prompt is, "Please suggest the best appointment date and time based on the user's preferences."

[0999] Based on the analysis results, the server recommends a suitable person. To obtain the recommended person's schedule, the server uses scheduling software. Specifically, it uses common scheduling software such as the Google Calendar API to retrieve the schedule information of both the user and the recommended person.

[1000] Based on the acquired schedule information, the server finds a time that is convenient for both the user and the recommended person. To automatically set an appointment at the found time, the server again uses the schedule management software and adds the appointment to the calendar. This series of processes allows the user to set appointments efficiently. The flow of the specific process in Example 3 will be explained using Figure 15.

[1001] Step 1:

[1002] The user enters their appointment preferences in natural language using a terminal. For example, they might enter a specific date, time, and format, such as, "I'd like to schedule a one-on-one appointment for next Monday." This input forms the basis for the next processing step.

[1003] Step 2:

[1004] The server passes the natural language input received from the user to a generative AI model. The generative AI model uses prompts to analyze the user's request. Specifically, it analyzes the input natural language to identify the date, time, and format of the appointment. This analysis result becomes the input for the next step.

[1005] Step 3:

[1006] The server recommends a suitable person based on the analysis results. Information about the recommended person is retrieved from the database. The server searches the database using the analysis results and selects the most suitable person. This recommendation result becomes the input for the next step.

[1007] Step 4:

[1008] The server uses scheduling software to retrieve the schedules of recommended individuals. Specifically, it uses the Google Calendar API to obtain schedule information for both the user and the recommended individuals. This schedule information will then be used as input for the next step.

[1009] Step 5:

[1010] The server uses the retrieved schedule information to find a time that works for both the user and the recommended person. The server compares their availability and determines the optimal appointment date and time. This determined date and time becomes the input for the next step.

[1011] Step 6:

[1012] The server automatically sets appointments based on the time it finds. The server uses the Google Calendar API to add appointments to the calendar at the determined date and time. This eliminates the need for users to manually adjust their schedules.

[1013] (Application Example 3)

[1014] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as a "server," and the headset-type terminal 314 will be referred to as a "terminal."

[1015] In modern organizations, efficiently scheduling appointments with the right person at the user's preferred date and time is crucial. However, traditional systems often require manual processes of checking the schedules of individuals within the organization based on the user's preferred date and time, and finding available time slots, which is time-consuming and laborious. Furthermore, the lack of functionality to automatically add confirmed appointments to the user's and the organization's personnel's calendars makes appointment management cumbersome.

[1016] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[1017] In this invention, the server includes means for inputting the user's experience and future goals; means for recommending appropriate individuals within the organization based on the relevant information; means for automatically setting appointments with the recommended individuals; means for inputting the user's desired date and time, checking the schedules of individuals within the organization, and suggesting available times; and means for automatically adding confirmed appointments to the calendars of the user and individuals within the organization. This makes it possible to efficiently set appointments at the date and time desired by the user and to automate appointment management.

[1018] A "user" is an individual or member of an organization who intends to use the system to schedule an appointment.

[1019] "Experience" refers to the knowledge, skills, and achievements a user has acquired in the past, and is a factor considered when setting up an appointment.

[1020] "Future goals" refer to specific objectives or plans that the user wishes to achieve, and are factors considered when setting up an appointment.

[1021] A "person recommendation system" is a function that selects and recommends appropriate individuals within an organization based on their experience and future goals.

[1022] The "appointment setting method" is a function that automatically sets appointments with recommended individuals based on the user's preferred date and time.

[1023] A "schedule" is a timetable that shows the planned activities and free time of individuals within an organization.

[1024] "Free time" refers to periods within an organization when a person does not have other appointments or activities, and is the time available for scheduling appointments.

[1025] A "schedule" is a tool for recording and managing the schedules of users and individuals within an organization.

[1026] The system for carrying out this invention comprises a user terminal and a server. The user terminal is a device such as a smartphone or tablet, which provides an interface for the user to input their experiences and future goals. The server receives input from the user and performs a person recommendation means for recommending individuals within the organization.

[1027] The server retrieves the characteristics of individuals within the organization from a database based on the user's input and recommends the appropriate person. In this process, a generative AI model is used to select the person best suited to the user's experience and goals.

[1028] To schedule an appointment with a recommended person, the server uses an appointment scheduling mechanism. When the user enters their preferred date and time, the server checks the schedules of individuals within the organization and suggests available times. This allows the user to efficiently schedule appointments.

[1029] Confirmed appointments are automatically added to the calendars of both the user and individuals within the organization by the server. This simplifies appointment management and makes it easier for both users and individuals within the organization to check their schedules.

[1030] For example, if a user enters "I would like to schedule an appointment with the person in charge for 3 PM next Wednesday," the server will check the person in charge's schedule, and if it confirms that 3 PM is available, it will notify the user and confirm the appointment.

[1031] An example of a prompt message would be, "I would like to schedule an appointment with the person in charge for 3 PM next Wednesday. Please check their availability and confirm the reservation."

[1032] In this way, users can efficiently schedule appointments at their desired time and time, and communicate smoothly with people within their organization.

[1033] The flow of the specific processing in Application Example 3 will be explained using Figure 16.

[1034] Step 1:

[1035] The user uses a device to enter their experience, future goals, and preferred appointment dates and times. The entered data is then sent from the device to the server.

[1036] Step 2:

[1037] The server initiates a process to recommend individuals within the organization based on the user's experience and goals. Using a generative AI model, it analyzes the user's input data and retrieves the characteristics of suitable individuals from the database. This allows it to select the person best suited to the user.

[1038] Step 3:

[1039] The server checks the schedules of individuals within the organization based on the user's preferred date and time to set up an appointment with the recommended person. It uses a schedule management API to retrieve the person's availability and matches it with the user's preferred date and time.

[1040] Step 4:

[1041] The server suggests available time slots to the user when it finds them. Once the user accepts the suggested time, the server confirms the appointment and automatically adds it to the user's and other relevant individuals' calendars. This streamlines appointment management.

[1042] Step 5:

[1043] The server sends notifications to the user and relevant individuals within the organization regarding confirmed appointments. The notification system is used to send messages containing appointment details, allowing both parties to confirm their schedules.

[1044] In this way, users can efficiently schedule appointments at their desired dates and times, and communicate smoothly with people within their organization.

[1045] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1046] "Example of form 1"

[1047] One embodiment of the present invention involves a system that includes an emotion engine that recognizes the user's emotions as a means of inputting the user's experiences and future goals. This emotion engine analyzes emotions from the user's text or voice input and feeds the results back to the system. For example, if a user inputs, "I have experience in project management, and in the future I would like to work on project management utilizing AI technology," the emotion engine reads the user's motivation and expectations from that text.

[1048] "Example of form 2"

[1049] Furthermore, some systems recommend individuals by taking into account the user's emotions, as recognized by an emotion engine. In this system, the emotion engine analyzes the results to infer what kind of people the user wants to interact with, and then recommends individuals based on that. For example, if the user shows positive emotions, the system will recommend individuals who are also positive.

[1050] "Example of form 3"

[1051] Furthermore, some appointment scheduling systems take into account the user's emotions, as recognized by an emotion engine. This system considers the user's emotional state and schedules appointments at a time and format appropriate to that state. For example, if a user is feeling stressed, the system might schedule an appointment during a time when they can relax.

[1052] The following describes the processing flow for each example of the form.

[1053] "Example of form 1"

[1054] Step 1: The user enters their experiences and future goals into the system via text or voice input.

[1055] Step 2: The emotion engine analyzes the user's emotions from their input. This analysis utilizes natural language processing and speech analysis technologies.

[1056] Step 3: The emotion engine feeds the analysis results back into the system. This feedback includes the user's emotional state and its intensity.

[1057] "Example of form 2"

[1058] Step 1: The emotion engine analyzes the user's emotions.

[1059] Step 2: Based on the analysis results of the emotion engine, the system infers what kind of people the user wants to interact with.

[1060] Step 3: Based on the prediction results, the system recommends a suitable person to the user.

[1061] "Example of form 3"

[1062] Step 1: The emotion engine analyzes the user's emotions.

[1063] Step 2: Based on the analysis results of the emotion engine, the system determines the appropriate timing and format for the user's emotional state.

[1064] Step 3: The system sets an appointment based on its assessment results.

[1065] (Example 1)

[1066] Next, we will describe Embodiment 1 of Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1067] Traditional systems could recommend the right person and schedule appointments based on the user's experience and goals, but they couldn't provide feedback that took the user's emotions into account. As a result, there was a lack of support that reflected the user's motivation and expectations.

[1068] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1069] In this invention, the server includes means for the user to input their experiences and future goals, means for recommending appropriate individuals within the group based on the relevant information, means for automatically setting appointments with the recommended individuals, means for analyzing the user's input information and recognizing their emotions, and means for providing feedback to the user based on the analysis results. This enables the provision of appropriate feedback that takes the user's emotions into consideration and supports the user in achieving their goals.

[1070] "A means for users to input experiences and future goals" refers to a device or software that provides an interface for users to input their past experiences and future goals in text format.

[1071] A "person recommendation system" is an algorithm or system that identifies and recommends appropriate individuals within a group based on information entered by the user.

[1072] An "appointment setting tool" is a device or software that has the function of automatically scheduling meetings or interviews with recommended individuals.

[1073] "Emotion analysis means" refers to a technology or system that analyzes user input information to recognize the user's emotions and motivations.

[1074] A "feedback tool" is a device or software that has the function of providing appropriate advice or information to the user based on the results of sentiment analysis.

[1075] This invention is a system that provides an interface for users to input their experiences and future goals. Users can input information in text format using a dedicated application on their terminal or a web browser. The input information is transmitted from the terminal to the server.

[1076] The server stores the received information in a database. This database can use a common relational database management system (RDBMS) such as MySQL or PostgreSQL. The stored information is analyzed by a person recommendation system to identify and recommend suitable individuals to the user.

[1077] Furthermore, the server uses sentiment analysis tools to analyze the user's emotions from their input information. This analysis utilizes a sentiment engine that leverages natural language processing (NLP) technology. Specifically, services such as Google Cloud Natural Language API and IBM Watson Natural Language Understanding can be used.

[1078] The analysis results are provided to the user through a feedback mechanism. This feedback is sent to the user's device as advice and support information to help them achieve their goals. The user can then review the feedback on their device and use it to guide their next actions.

[1079] For example, if a user enters "I have experience in project management and would like to work on project management using AI technology in the future," the sentiment analysis tool will read the user's motivation and expectations from that text, and the feedback tool will provide advice based on that.

[1080] An example of a prompt for a generative AI model is, "Analyze the user's input to understand their motivation and expectations, and generate feedback." By using this prompt, the AI ​​model can generate feedback that takes the user's emotions into account.

[1081] The flow of the specific processing in Example 1 will be explained using Figure 17.

[1082] Step 1:

[1083] Users access the user interface via a dedicated application or web browser using their device. Users enter their experiences and future goals into text boxes. Once they have finished entering the data, they click the "Submit" button, sending the data from their device to the server. The input data consists of text information about the user's experiences and goals.

[1084] Step 2:

[1085] The server receives user input data sent from the terminal. The received data is stored in the database. The server establishes a database connection and executes SQL queries to save the user input data. The input is the user's text information, and the output is the information stored in the database.

[1086] Step 3:

[1087] The server passes stored user input data to the sentiment analysis tool. The sentiment analysis tool uses natural language processing technology to analyze emotions from the text. The server sends an API request to the sentiment engine and receives the analysis results. The input is text information obtained from the database, and the output is the analysis result regarding the user's emotions.

[1088] Step 4:

[1089] The server provides feedback to the user using a feedback mechanism based on the analysis results obtained from the sentiment analysis mechanism. The server generates a feedback message based on the analysis results and sends it to the terminal. The user can view the feedback message on the terminal. The input is the result of the sentiment analysis, and the output is the feedback message provided to the user.

[1090] (Application Example 1)

[1091] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1092] In today's information society, it is crucial to recommend appropriate people and products based on users' experiences and future goals. However, conventional systems often fail to consider user emotions when making recommendations, making it difficult to meet user expectations.

[1093] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1094] In this invention, the server includes means for inputting the user's experiences and future goals, means for recommending appropriate individuals within the group organization based on the relevant information, means for automatically setting appointments with the recommended individuals, means for analyzing the user's input information and emotions, and means for recommending products based on the analysis results. This enables personalized recommendations that take the user's emotions into consideration.

[1095] "Means for inputting user experiences and future goals" refers to a feature that provides an interface for users to input their past experiences and future goals in text or voice.

[1096] "Person recommendation methods" are functions that identify and recommend appropriate individuals within a group organization based on user input information.

[1097] The "appointment scheduling method" is a function that automatically schedules meetings and interviews with recommended individuals.

[1098] "Emotion analysis tools" are functions that analyze user input information to evaluate the user's emotions and motivation.

[1099] A "product recommendation method" is a function that selects and recommends the most suitable product to the user based on the results of sentiment analysis.

[1100] The system for implementing this invention consists of a terminal equipped with an interface for inputting the user's experiences and future goals, and a server that analyzes the input information. The terminal is a device such as a smartphone or computer, and allows the user to input information in text or voice. The server uses software such as Python or TensorFlow to analyze the user's input information with a natural language processing library (such as NLTK) and perform sentiment analysis.

[1101] The server is equipped with a product recommendation engine that recommends the most suitable products to users based on the results of sentiment analysis. This engine selects relevant products while considering the user's purchasing intent and expectations. Furthermore, the server also has a function to recommend appropriate individuals within the group organization and automatically set up appointments based on the user's input information.

[1102] For example, if a user inputs "I've recently become interested in fitness and am looking for fitness-related gadgets" using their device, the server analyzes this information and determines that the user has a high level of interest. Based on this, it recommends fitness bands and smartwatches. Similarly, if a user inputs "I have experience in project management and would like to work on project management using AI technology in the future," the server recommends appropriate experts and sets up interview appointments.

[1103] An example of a prompt to input into the generative AI model is: "Analyze the user's input text and recommend products that will increase their purchase intent. Input: 'I've recently become interested in fitness and am looking for fitness-related gadgets.'"

[1104] The flow of a specific process in Application Example 1 will be explained using Figure 18.

[1105] Step 1:

[1106] Users input their experiences and future goals using text or voice via a device. The input data is sent from the device to the server. The input data includes information about the user's interests and goals.

[1107] Step 2:

[1108] The server analyzes the received input data using a natural language processing library (such as NLTK). The analysis extracts the user's intent and emotions. Specifically, this involves text tokenization, part-of-speech tagging, and the calculation of an emotion score.

[1109] Step 3:

[1110] The server uses a generative AI model to select the most suitable products for the user based on the results of sentiment analysis. It uses sentiment scores as input, and the product recommendation engine lists relevant products. The output is a list of products that match the user's interests.

[1111] Step 4:

[1112] The server recommends appropriate individuals within the group organization based on user input. Using the user's goals and experience as input, the person recommendation engine identifies suitable experts. The output is information about the recommended individuals.

[1113] Step 5:

[1114] The server automatically schedules appointments with recommended individuals. Using the recommended person's information and the user's preferred date and time as input, the scheduling algorithm determines the optimal date and time. The output is the details of the scheduled appointment.

[1115] (Example 2)

[1116] Next, we will describe Example 2 of the Form Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1117] In modern organizations, it is crucial to recommend the right person quickly and accurately, but traditional systems struggle to adequately consider users' feelings and preferences when making recommendations. Furthermore, scheduling appointments with recommended individuals is often done manually, hindering efficient talent utilization.

[1118] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1119] In this invention, the server includes means for inputting user information, means for recommending appropriate individuals within the organization based on the relevant information, means for automatically setting appointments with the recommended individuals, means for analyzing the user's emotions, and means for recommending individuals based on the analysis results. This enables the recommendation of appropriate personnel that takes into account the user's emotions and wishes, and efficient appointment setting.

[1120] "Means for inputting user information" refers to an interface that allows users to input their own information and desired conditions into the system.

[1121] A "person recommendation system" refers to an algorithm or process that identifies and recommends suitable individuals within an organization based on the information entered.

[1122] The "appointment scheduling method" is a function that automatically schedules meetings and interviews with recommended individuals.

[1123] "Methods for analyzing user emotions" refer to analytical techniques that identify a user's emotional state based on their input data.

[1124] "A method for recommending individuals based on analysis results" refers to a process for recommending the most suitable individuals by taking into account the results of the user's sentiment analysis.

[1125] "Methods for learning individual characteristics from the deliverables of members" refers to techniques for learning the characteristics and skills of individuals by analyzing the deliverables of tasks and projects that members of an organization have performed in the past.

[1126] An "information recording device" is a database or storage system used to save the characteristics and skills of a person that have been learned.

[1127] An "individual interview" is a form of interview or meeting conducted one-on-one between the user and the recommended person.

[1128] A description of embodiments for carrying out this invention will be given.

[1129] The server provides an interface for users to input their information. Through this interface, users can enter their information and preferences. The entered information is stored in a database on the server.

[1130] The server uses an AI algorithm as a means of recommending individuals. This algorithm analyzes the output of its members using machine learning frameworks such as TensorFlow and PyTorch, and learns the characteristics of each individual. The learned characteristics are registered in an information recording device.

[1131] The device uses Affectiva or Microsoft Azure sentiment analysis APIs to analyze the user's emotions. Based on text and voice data entered by the user, it identifies the user's current emotional state. This analysis result is then sent to the server.

[1132] The server then performs a recommendation process based on the analysis results. This allows it to identify and recommend the person who best matches the user's preferences and emotional state.

[1133] Furthermore, the server automatically schedules interviews and meetings with recommended individuals using an appointment scheduling mechanism. This process allows users to efficiently connect with suitable personnel.

[1134] As a concrete example, if a user enters the prompt "Please recommend the best employee for the AI ​​project. I am motivated," the server will use an AI algorithm to analyze employee data and list motivated AI engineers. This list will be displayed on the user's device, and the user can select the most suitable employee from among them.

[1135] The flow of the specific processing in Example 2 will be explained using Figure 19.

[1136] Step 1:

[1137] Users input their information and preferences through the system interface. This information is sent to the server and stored in a database. This includes project type and required skill set.

[1138] Step 2:

[1139] The server collects data from a database regarding the past projects and achievements of members within the organization. Based on the collected data, an AI algorithm using TensorFlow or PyTorch learns the characteristics of each member. Through this process, the skills and characteristics of each member are registered in the information recording device.

[1140] Step 3:

[1141] The device uses Affectiva or Microsoft Azure sentiment analysis APIs to analyze the user's emotions. Based on text and voice data entered by the user, it identifies the current emotional state. The analysis results are sent to the server as data indicating the user's emotional state.

[1142] Step 4:

[1143] The server executes an AI algorithm based on the user's preferences and sentiment analysis results. This identifies the most suitable members for the user's criteria and generates a recommendation list. The recommendation list takes into account the user's preferences and emotional state.

[1144] Step 5:

[1145] The server presents the generated recommendation list to the user. The user can then select project members based on this list. Specifically, the list displays the member's name, skill set, and past achievements.

[1146] Step 6:

[1147] The server automatically schedules appointments with selected members. Using the appointment scheduling mechanism, it efficiently coordinates interview and meeting schedules and notifies the user. This allows the user to quickly connect with the appropriate personnel.

[1148] (Application Example 2)

[1149] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as a "server," and the headset-type terminal 314 will be referred to as a "terminal."

[1150] In modern manufacturing environments, proper personnel allocation and team formation are crucial for improving production efficiency. However, traditional methods have made it difficult to recommend personnel that fully consider the characteristics and emotional states of workers, thus hindering the creation of optimal teams. This has resulted in challenges such as decreased production efficiency and reduced worker motivation.

[1151] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1152] In this invention, the server includes means for inputting the user's experience and future goals, means for recommending appropriate individuals within the organization based on the relevant information, means for automatically setting appointments with the recommended individuals, means for learning the characteristics of workers and registering them in a database, and means for considering the user's emotional state using emotion analysis means and recommending the most suitable person. This enables optimal personnel placement and team formation that takes into account the characteristics and emotional state of workers.

[1153] "A means of inputting user experiences and future goals" refers to an interface that allows users to input their past experiences and future goals into the system.

[1154] A "person recommendation system" is a function that includes an algorithm for selecting and recommending appropriate individuals within an organization based on the information entered.

[1155] The "appointment scheduling method" is a function that automatically adjusts and sets the date and time for meetings or interviews with recommended individuals.

[1156] "Methods for learning worker characteristics and registering them in a database" refers to the process by which AI analyzes workers' past performance and skills and saves the results in a database.

[1157] "Emotional analysis means" refers to technology that analyzes a user's current emotional state and reflects the results in person recommendations.

[1158] The system for carrying out this invention includes a server, a user terminal, and a database. The server provides an interface for users to input their experiences and future goals, and recommends appropriate individuals within the organization based on the input information. The server uses an AI algorithm to learn the characteristics of workers and registers them in the database. Furthermore, it uses sentiment analysis means to analyze the user's emotional state and reflects the results in person recommendations.

[1159] The server implements AI algorithms using Python and utilizes the OpenAI API for sentiment analysis. The database stores data on workers' skills, past performance, and emotional states. The user terminal receives recommendation results from the server and automatically sets up appointments with the recommended individuals.

[1160] As a concrete example, when setting up a new production line in a factory, the server identifies workers who have performed well in past projects, confirms that their current emotional state is motivated, and recommends them as leaders. An example of a prompt to input into the generative AI model would be, "Recommend the best worker to set up the new production line. Please consider past performance and current emotional state."

[1161] The flow of a specific process in Application Example 2 will be explained using Figure 20.

[1162] Step 1:

[1163] The user uses a terminal to input their experiences and future goals. The entered information is sent to the server. The server receives this information and stores it in a database.

[1164] Step 2:

[1165] The server uses an AI algorithm to recommend suitable individuals within the organization based on user information stored in the database. The AI ​​algorithm analyzes the worker's past performance and skills to select the person best suited to the user's goals. The output of this process is a list of recommended individuals.

[1166] Step 3:

[1167] The server analyzes the user's emotional state using emotion analysis tools. Based on the user's input information and past data, it infers their current emotional state. The analysis results are reflected in the person recommendation. Specifically, users who show motivated emotions will be recommended similarly motivated individuals.

[1168] Step 4:

[1169] The server automatically sets up appointments with recommended individuals. It selects the optimal date and time, taking into account the user's schedule and preferences. The scheduled appointment information is sent to the user's terminal, and the user is notified.

[1170] Step 5:

[1171] Users can view recommendation results and appointment information through their terminal. They can change or cancel appointments as needed. The server updates the database in response to user actions and sends notifications to relevant individuals.

[1172] (Example 3)

[1173] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1174] Traditional systems may increase the user's psychological burden by scheduling appointments without considering their emotional state. Furthermore, they may not adequately reflect the user's experience and goals when recommending appropriate individuals. This presents a challenge in providing users with optimal communication opportunities.

[1175] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[1176] In this invention, the server includes means for inputting the user's experiences and future goals, means for recommending appropriate individuals within the organization based on the relevant information, means for automatically setting appointments with the recommended individuals, means for analyzing the user's emotional state, and means for determining the optimal appointment time based on the emotional state. This makes it possible to provide optimal communication opportunities that take the user's emotional state into consideration.

[1177] "A means of inputting user experiences and future goals" refers to a function that provides an interface for users to input their past experiences and future goals into the system.

[1178] "Personnel recommendation methods" refer to algorithms and processes that select and recommend appropriate individuals within an organization based on user input information.

[1179] The "scheduling method" is a function that automatically coordinates and sets schedules with recommended individuals.

[1180] "Emotional analysis methods" are technologies that analyze a user's input data and past behavior to infer their current emotional state.

[1181] "Methods for determining the optimal appointment time based on emotional state" refers to a process that takes into account the user's emotional state and selects the optimal time to reduce psychological burden.

[1182] As an embodiment of this invention, the following system is constructed.

[1183] Users input their experiences and future goals through a terminal. This allows the system to understand the user's needs and desires. The entered information is sent to a server and stored in a database.

[1184] The server recommends suitable individuals within the organization based on information received from the user. As a means of recommending individuals, the server utilizes characteristic information of members registered in a database. This makes it possible to select the person best suited to the user's needs.

[1185] Next, the server uses scheduling software such as the Google Calendar API to automatically schedule appointments with recommended individuals. When a user enters a prompt such as, "I'd like to schedule a 1-on-1 appointment for next Monday," the server compares the user's and the recommended individuals' schedules, finds a common time slot, and schedules the appointment.

[1186] Furthermore, the server uses a generative AI model to analyze the user's emotional state. This emotional analysis tool analyzes the user's input data and past behavior to infer their current emotional state. For example, if the server determines that the user is experiencing stress, it uses this information to select the optimal time to alleviate their psychological burden and schedule activities accordingly.

[1187] In this way, users can obtain the optimal communication opportunity that takes their own emotional state into consideration. The flow of the specific processing in Example 3 will be explained using Figure 21.

[1188] Step 1:

[1189] Users input their experiences and future goals through their terminal. The entered information is sent to the server as prompt messages. For example, specific requests such as "I would like to schedule a one-on-one appointment for next Monday" might be entered. This input data is used as foundational data to understand the user's needs.

[1190] Step 2:

[1191] The server analyzes the prompt received from the user and recommends the appropriate person within the organization. The server accesses a database and, based on member characteristics, selects the person best suited to the user's needs. This process analyzes the user's input data and generates a list of recommended individuals.

[1192] Step 3:

[1193] The server uses the Google Calendar API to retrieve the schedules of the user and the recommended person. The server compares the schedules of both parties to find common free time. In this step, the schedule data is analyzed to determine the best time for the appointment.

[1194] Step 4:

[1195] The server uses a generative AI model to analyze the user's emotional state. Based on the user's input data and past behavior, the emotion analysis tool infers the user's current emotions. For example, if it determines that the user is feeling stressed, this information is taken into consideration in the next step.

[1196] Step 5:

[1197] The server determines the optimal appointment time based on the user's emotional state. To reduce psychological burden, it selects a time when the user can relax. This step takes into account the results of the emotional analysis to select the optimal time.

[1198] Step 6:

[1199] The server notifies the user and the recommended person of the details of the confirmed appointment. The notification is sent via email or calendar reminder. This allows the user and the recommended person to check the appointment details and have an opportunity to communicate.

[1200] (Application Example 3)

[1201] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as a "server," and the headset-type terminal 314 will be referred to as a "terminal."

[1202] In today's business environment, communication that takes into account the user's emotional state is essential. However, traditional appointment scheduling systems fail to consider user emotions, making it difficult to schedule appointments at the optimal time. This can lead to decreased user satisfaction and hinder efficient communication.

[1203] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[1204] In this invention, the server includes means for inputting the user's experience and future goals, means for recommending appropriate individuals within the organization based on the relevant information, means for automatically setting appointments with the recommended individuals, and means for recognizing the user's emotional state and adjusting the timing of appointments based on that emotional state. This makes it possible to set appointments at the optimal timing according to the user's emotional state, thereby improving user satisfaction.

[1205] A "user" is an individual or group that uses the system to schedule an appointment.

[1206] "Experience" is a general term for the knowledge, skills, and experiences a user has acquired in the past.

[1207] "Future goals" refer to the future plans and objectives that the user hopes to achieve.

[1208] "Means of input" refers to the methods or devices that users use to provide information to a system.

[1209] "Within the organization" refers to the internal workings of a specific company or group.

[1210] The "right person" is the individual who best matches the user's requirements and conditions.

[1211] A "recommendation method for recommending individuals" refers to a method or device for selecting and suggesting the most suitable person based on user information.

[1212] An "appointment" is a reservation for a meeting or conference at a specific date and time.

[1213] An "automatic appointment scheduling method" refers to a method or device for a system to automatically determine appointments based on user conditions.

[1214] "Emotional state" refers to the user's psychological state or mood.

[1215] "Emotion recognition means for recognizing and adjusting appointment timing based on the emotional state" refers to a method or device for analyzing a user's emotions and determining the optimal appointment time based on the results.

[1216] The system for carrying out this invention includes a terminal for inputting the user's experience and future goals, a server for recommending appropriate individuals within the organization, and a server for automatically scheduling appointments with the recommended individuals. Furthermore, it includes emotion recognition means for recognizing the user's emotional state and adjusting the timing of appointments based on that emotional state.

[1217] The server receives information entered by the user through the terminal and analyzes the user's emotional state using a generative AI model. During this process, it uses an emotion recognition API (e.g., Microsoft Azure Emotion API) to identify the user's emotions. Next, the server uses scheduling software (e.g., Google Calendar API) to retrieve the availability of appropriate individuals within the organization.

[1218] The server calculates the optimal appointment timing based on the user's emotional state and sets the appointment accordingly. This process allows for appointment scheduling at a time that suits the user's emotional state, thereby improving user satisfaction.

[1219] For example, if a user enters "I'd like to discuss security next Monday" into their device, the server uses an emotion recognition API to analyze the user's stress level. If the server determines that the stress level is high, it checks the availability of a support staff member and schedules an appointment for a more relaxed afternoon time.

[1220] An example of a prompt message would be, "If the user is feeling stressed, please tell me how to schedule an appointment during a time when they can relax."

[1221] The flow of the specific processing in Application Example 3 will be explained using Figure 22.

[1222] Step 1:

[1223] The user enters their experience, future goals, and desired appointment date and time via a terminal. The entered data is sent to the server. The server receives this data and prepares to analyze the user's request.

[1224] Step 2:

[1225] The server uses an emotion recognition API to analyze the user's emotional state. The input includes user voice and text data. The API processes this data and outputs the user's emotional state (e.g., stress level). Based on this output, the server understands the user's current emotional state.

[1226] Step 3:

[1227] The server runs a person recommendation algorithm that considers the user's input data and emotional state to recommend the right person within the organization. The inputs used are the user's experience, goals, and emotional state. The algorithm processes this data and outputs the most suitable person. Based on this output, the server identifies the recommended person.

[1228] Step 4:

[1229] The server uses scheduling software to retrieve the availability of the recommended person. The input includes the recommended person's ID and schedule information. The software processes this data and outputs their availability. Based on this output, the server identifies potential appointment times.

[1230] Step 5:

[1231] The server calculates the optimal appointment timing based on the user's emotional state. The inputs used are the user's emotional state and the availability of the recommended person. The server processes this data and outputs the optimal appointment time. Based on this output, the server automatically schedules the appointment.

[1232] Step 6:

[1233] The server notifies the user and the recommended person of the details of the scheduled appointment. The inputs used are the date, time, location, and participant information of the appointment. The server processes this data and outputs a notification message. The user and the recommended person receive this notification and confirm the appointment details.

[1234] (Other examples)

[1235] Since this is the same as the specific processing described in the other embodiments of the first embodiment above, the explanation will be omitted.

[1236] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1237] The data generation model 58 is a form of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1238] Other examples of generative AI include Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are some examples.

[1239] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1240] [Fourth Embodiment]

[1241] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1242] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1243] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1244] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1245] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1246] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1247] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1248] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1249] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1250] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1251] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1252] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1253] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[1254] "Example of form 1"

[1255] The system of the present invention provides a means for users to input their own experiences and future goals. Specifically, it allows users to input their experiences and goals in text format through a user interface. For example, if a user inputs "I have experience in project management and in the future I would like to work on project management utilizing AI technology," this information is stored in the system.

[1256] "Example of form 2"

[1257] Next, the personnel recommendation system recommends appropriate individuals within the group companies based on the input information. Specifically, it uses an AI algorithm to learn the characteristics of employees from their output and registers them in a database. For example, the AI ​​learns from an employee's past projects and achievements that the employee is proficient in AI technology and recommends that employee.

[1258] "Example of form 3"

[1259] Finally, the appointment scheduling method automatically sets up appointments with recommended individuals. Specifically, it sets up appointments such as one-on-one meetings according to the user's preferences. For example, if a user enters, "I would like to schedule a one-on-one appointment for next Monday," the system compares the schedules of the recommended individuals with the user's, finds a time that works for both parties, and sets up the appointment.

[1260] The following describes the processing flow for each example of the form.

[1261] "Example of form 1"

[1262] Step 1: The user enters their experience and future goals in text format through the system's user interface. For example, they might enter, "I have experience in project management, and in the future I would like to work on project management utilizing AI technology." Step 2: The entered information is saved in the system.

[1263] "Example of form 2"

[1264] Step 1: The personnel recommendation system uses an AI algorithm based on stored information to learn about individual characteristics from employee output.

[1265] Step 2: The learned characteristics are registered in the database.

[1266] Step 3: The AI ​​learns from an employee's past projects and achievements whether that employee is proficient in AI technology and recommends that employee.

[1267] "Example of form 3"

[1268] Step 1: The user enters "I would like to schedule a 1-on-1 appointment for next Monday."

[1269] Step 2: The appointment scheduling system compares the schedules of the recommended individuals with those of the user.

[1270] Step 3: Find a time that works for both parties and set up an appointment.

[1271] (Example 1)

[1272] Next, we will describe Embodiment 1 of Example Form 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1273] Conventional systems struggled to provide appropriate advice based on users' experiences and goals, and in particular, they were unable to effectively utilize the generation of prompts and responses using generative AI models. As a result, they lacked sufficient concrete information to support users' career development.

[1274] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1275] In this invention, the server includes means for inputting the user's experiences and future goals, means for generating prompt sentences to be input to a generative AI model based on the relevant information, and means for sending the generated prompt sentences to the generative AI model and receiving a response. This makes it possible to utilize the generative AI model based on the user's input and provide the user with appropriate advice.

[1276] "A means of inputting user experiences and future goals" refers to a function that provides an interface for users to input their past experiences and future goals in text format.

[1277] "Means for generating prompt text to input into a generative AI model" refers to a function that analyzes user input data and creates prompt text to provide information to the generative AI model in the most optimal format.

[1278] "Means for sending generated prompt sentences to a generation AI model and receiving responses" refers to a communication function for sending generated prompt sentences to a generation AI model and receiving its responses.

[1279] "A means of providing appropriate advice to users" refers to a function that presents users with specific advice to support their career development, based on responses received from a generative AI model.

[1280] This invention is a system in which a user inputs their own experiences and future goals, and then utilizes a generated AI model to provide appropriate advice based on that input. The following describes a specific form for implementing this system.

[1281] Users access the user interface through a web browser or mobile application. This interface provides a means for users to input their experiences and goals in text format. For example, a user might input, "I have experience in project management, and in the future I would like to work on project management utilizing AI technology."

[1282] The terminal sends the data entered by the user to the server. Typically, this data is packaged in JSON format and sent as an HTTP request. The server parses the received data and generates prompts for input into the AI ​​model based on the user's input. Programming languages ​​such as Python and Java are used for this process.

[1283] The generated prompt is sent to the AI ​​model. The server accesses the AI ​​model via an API and provides the prompt as input. For example, it can generate a prompt such as, "The user has project management experience and is interested in projects utilizing AI technology. What skills should they learn?"

[1284] Upon receiving a response from the generated AI model, the server provides appropriate advice to the user based on that information. This advice includes specific information to support the user's career development. The terminal displays the information received from the server in the user interface, allowing the user to view the advice and recommendations on the screen.

[1285] This system aims to provide users with specific and useful advice by utilizing a generated AI model based on user input.

[1286] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1287] Step 1:

[1288] The user inputs information. Users access the user interface via a web browser or mobile application and input their experiences and future goals in text format. The entered data is then transmitted to the device as information related to the user's career development.

[1289] Step 2:

[1290] The device sends data. The device converts the text data entered by the user into JSON format and sends it to the server as an HTTP request. This process verifies the format of the input data to maintain data integrity.

[1291] Step 3:

[1292] The server receives the data. The server receives the HTTP request sent from the terminal and extracts the user's input data from the request body. The server verifies the integrity of the data and checks for any invalid data.

[1293] Step 4:

[1294] The server generates prompt text. The server analyzes the received user data and generates prompt text to input into the AI ​​model. This process uses natural language processing techniques to appropriately summarize the user's input and format it as prompt text.

[1295] Step 5:

[1296] The server sends a prompt message to the generating AI model. The server sends the generated prompt message to the generating AI model via the API. The generating AI model receives the prompt message as input and generates advice regarding the user's career development.

[1297] Step 6:

[1298] The server receives the response from the generated AI model. The server receives the response from the generated AI model and analyzes its contents. The response includes specific advice and recommendations to support the user's career development.

[1299] Step 7:

[1300] The terminal displays the results to the user. The terminal displays the advice received from the server on the user interface. The user can review the advice and recommendations on the screen and use them to help with their future career development.

[1301] (Application Example 1)

[1302] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1303] In modern society, it is difficult to efficiently provide appropriate information based on the individual user's experiences and future goals. In particular, there is a demand for personalized information delivery that meets the diverse needs of users, but this is difficult to achieve with conventional systems. Therefore, there is a need for a system that generates relevant information based on user input and delivers it appropriately.

[1304] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1305] In this invention, the server includes means for inputting the user's experiences and future goals, generation means for generating relevant information based on the relevant information, and distribution means for delivering the generated information to the user. This enables the generation and delivery of information tailored to the individual needs of the user.

[1306] "A means of inputting user experiences and future goals" refers to a function that provides an interface for users to input their past experiences and future goals in text format.

[1307] "Generating means for generating related information based on relevant information" refers to a function that processes information entered by the user to generate related content and data.

[1308] "A means of delivering generated information to users" refers to a function that provides generated content and data to users in an appropriate format.

[1309] A "generative AI model" is an artificial intelligence model used to generate relevant information based on user input.

[1310] A "prompt statement" is an instruction given to a generative AI model, used to determine the content and format of the information that will be generated.

[1311] To implement this invention, an application installed on the user's device is used. The user uses a device such as a smartphone or tablet to input their experiences and future goals in text format. The entered information is sent to a server and stored in a database.

[1312] The server generates relevant information using a generative AI model based on the stored information. This generative AI model can use, for example, OpenAI's GPT. The generated information is selected according to the user's interests and needs and delivered to the user's device in an appropriate format.

[1313] For example, if a user enters "I am interested in project management using AI technology," the server will generate content such as "the latest trends in project management using AI" and "success stories of AI project management" and deliver it to the user.

[1314] An example of a prompt message is: "User experience: Project management. Goal: Project management using AI technology. Generate relevant content."

[1315] In this way, it becomes possible to generate and deliver information tailored to the individual needs of users.

[1316] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1317] Step 1:

[1318] The user launches an application on their device and enters their experiences and future goals in text format. The entered information is sent from the device to the server. The input data consists of text information about the user's experiences and goals.

[1319] Step 2:

[1320] The server stores the received user input information in a database. During this process, the input data is converted to an appropriate format before being stored in the database. The database also records each user's experience and goals.

[1321] Step 3:

[1322] The server uses a generative AI model to generate relevant information based on stored user information. Specifically, it inputs prompt statements into the generative AI model and generates relevant content. The input is the prompt statement, and the output is the generated content.

[1323] Step 4:

[1324] The server sorts the generated content according to the user's interests and needs. The sorted information is filtered to be useful to the user. The input is the generated content, and the output is the sorted content.

[1325] Step 5:

[1326] The server delivers the selected content to the user's device. The user can view the delivered information on their device. The input is the selected content, and the output is the information displayed on the user's device.

[1327] (Example 2)

[1328] Next, we will describe Example 2 of the morphological example. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1329] In modern organizations, quickly and accurately finding the right people for a project is crucial, but selecting the right individuals from a vast amount of data is difficult. Furthermore, efficiently scheduling meetings with selected individuals is also a challenge.

[1330] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1331] In this invention, the server includes means for inputting the user's experience and future goals into an information processing device, means for recommending appropriate individuals within the organization based on the relevant information, and means for automatically setting up meetings with the recommended individuals. This makes it possible to quickly recommend the most suitable personnel for a project and efficiently set up meetings.

[1332] An "information processing device" is a device that receives input from a user and processes the data.

[1333] A "user" is an entity that uses a system to input information and obtain results.

[1334] "Experience" is a general term for the knowledge and skills a user has acquired in the past.

[1335] "Future goals" refer to the future state or outcome that the user hopes to achieve.

[1336] An "organization" is a group of members who come together to achieve a specific purpose.

[1337] A "personnel recommendation system" is a method for selecting appropriate individuals within an organization based on the information entered.

[1338] "Deliverables" is a general term for the results obtained from past work or projects undertaken by the team members.

[1339] An "information recording device" is a device that can store data and retrieve it as needed.

[1340] A "meeting scheduling mechanism" is a means for automatically scheduling meetings with recommended individuals.

[1341] A "private meeting" is a meeting held one-on-one with a specific person.

[1342] As an embodiment of this invention, the following system is constructed.

[1343] The server functions as an information processing device, receiving input from users. Users input their experiences and future goals through a terminal. Based on this information, the server performs a personnel recommendation system to recommend suitable individuals within the organization. This process involves using AI algorithms to learn characteristics from the deliverables of members and registering them in an information recording device. Specifically, machine learning frameworks such as TensorFlow and PyTorch are used to analyze data and build models.

[1344] The terminal receives prompt messages from the user and sends them to the server. For example, a prompt message such as "Please recommend an employee who is proficient in AI technology" might be entered. Based on this prompt message, the server uses a pre-trained AI model to recommend the most suitable employee.

[1345] Furthermore, the server includes a meeting scheduling mechanism that automatically arranges meetings with recommended individuals. This allows users to efficiently find suitable personnel for their projects and quickly schedule necessary meetings. This system is expected to optimize talent utilization within organizations and improve project success rates.

[1346] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1347] Step 1:

[1348] Users input their experiences and future goals through their terminals. This information is sent to the server as foundational data to identify the skills and characteristics required for the project. The input information is transmitted to the server in text format.

[1349] Step 2:

[1350] The server uses the received user information to collect relevant data from the organization's member database. Specifically, it uses SQL queries to extract data on members' past projects and achievements. This data serves as input for analysis by AI algorithms.

[1351] Step 3:

[1352] The server preprocesses the collected data and converts it into a format usable by the AI ​​model. For example, it converts text data into numerical vectors and imputes missing values. This process uses data processing libraries such as Pandas and NumPy. The preprocessed data is then used as input for the AI ​​model.

[1353] Step 4:

[1354] The server runs an AI model using pre-processed data to identify members who meet the user's requirements. Specifically, it analyzes the data using a neural network model built with TensorFlow or PyTorch and recommends the most suitable individuals. This result is generated as a recommendation list.

[1355] Step 5:

[1356] The server sends the generated recommendation list to the terminal. The user reviews this list via the terminal and selects suitable personnel for the project. The recommendation list includes information such as the names, skills, and past achievements of the members.

[1357] Step 6:

[1358] The server automatically schedules meetings with individuals selected by the user. Specifically, it uses a calendar API to coordinate the schedules of the user and selected members and set up meetings. This allows users to efficiently schedule meetings and move projects forward.

[1359] (Application Example 2)

[1360] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1361] In modern organizations, quickly identifying the right people and assigning them to the right tasks is a critical challenge. However, traditional methods make it difficult to accurately understand the characteristics and skills of individual workers and select the most suitable individuals. Furthermore, it is difficult to monitor work progress in real time and reassign workers as needed. This can lead to decreased work efficiency and wasted resources.

[1362] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1363] In this invention, the server includes means for inputting the user's experience and future goals, means for recommending appropriate individuals within the organization based on the relevant information, means for automatically setting appointments with the recommended individuals, means for recommending the most suitable workers according to the work content, and means for analyzing the progress of work and the necessary skills in real time. This enables the optimal allocation of personnel within the organization, leading to improved work efficiency and effective use of resources.

[1364] "A means of inputting user experiences and future goals" refers to an interface for inputting data about individual users' past experiences and goals they wish to achieve in the future.

[1365] A "personnel recommendation system that recommends appropriate individuals within an organization based on relevant information" is an algorithm that analyzes the input information and selects and recommends the person within the organization who is most suitable for that information.

[1366] "An appointment scheduling method that automatically sets up appointments with recommended individuals" refers to a system that automatically adjusts and sets the date and time of meetings or interviews between recommended individuals and users.

[1367] "A means of recommending the most suitable worker according to the work content" refers to a function for selecting and recommending workers who possess the most suitable skills and experience for a particular task.

[1368] "Means for analyzing work progress and required skills in real time" refers to technologies for monitoring and analyzing the progress of work and the skills required for that work in real time.

[1369] To implement this invention, it is necessary to build a system in which a server plays a central role. The server provides an interface for users to input their experiences and future goals, and runs an AI algorithm to recommend suitable individuals within the organization based on the input information. Specifically, an AI model is built using a programming language such as Python, and a database management system (e.g., MySQL) is used to manage the characteristics and skill sets of individuals within the organization.

[1370] The server uses a calendar API and other tools to adjust schedules and automatically set appointments with recommended individuals. It also analyzes work progress and required skills in real time to recommend the most suitable worker for each task. This requires software to collect and analyze data from sensors mounted on robots within the factory.

[1371] As a concrete example, if the installation of a specific part is delayed in the assembly process of a certain product, the server will recommend a worker who is familiar with that process. An example of a prompt to the generating AI model might be: "The installation of part Y is delayed in the assembly process of product X. Please recommend the most suitable worker for installing part Y."

[1372] In this way, the server enables the optimal allocation of personnel within the organization, improving work efficiency and making effective use of resources.

[1373] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1374] Step 1:

[1375] The server provides an interface for users to input their experiences and future goals. Users enter past projects and goals they wish to achieve. The entered data is sent to the server and stored in the database.

[1376] Step 2:

[1377] The server executes an AI algorithm to recommend suitable individuals within the organization based on the input information. The server retrieves the characteristics and skill sets of individuals within the organization from a database and compares them with the input information using a generative AI model. This allows it to select the most suitable individuals and generate a recommendation list.

[1378] Step 3:

[1379] The server automatically schedules appointments with recommended individuals. Using a calendar API, the server coordinates the schedules of both the recommended person and the user to select a suitable date and time. The selected date and time are then notified to both the user and the recommended person.

[1380] Step 4:

[1381] The server analyzes the progress of a task and the required skills in real time to recommend the most suitable worker for that task. The server collects data from sensors mounted on robots within the factory to evaluate the progress of the task. It compares the required skills with the skill sets of the workers to select the most suitable worker.

[1382] Step 5:

[1383] The server generates prompts for the AI ​​model and recommends workers as needed. For example, it generates a prompt such as, "The installation of part Y is delayed in the assembly process of product X. Please recommend the most suitable worker for installing part Y," and inputs it into the AI ​​model. This then recommends the most suitable worker.

[1384] (Example 3)

[1385] Next, we will describe Embodiment 3 of Example 3. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1386] Traditional appointment scheduling systems required users to manually adjust schedules, which was time-consuming and laborious. Furthermore, the process of finding the right person was cumbersome, hindering efficient communication.

[1387] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[1388] In this invention, the server includes means for inputting user requests in natural language, means for analyzing user requests using a generative AI model, and means for recommending appropriate individuals based on the analysis results. This enables users to efficiently set appointments and communicate quickly with appropriate individuals.

[1389] "A means of inputting user requests in natural language" refers to a function that provides an interface for users to input their desired appointment date, time, and format in natural language.

[1390] "Methods for analyzing user requests using generative AI models" refers to a function that uses generative AI models to analyze natural language requests entered by users and to identify specific appointment dates, times, and formats.

[1391] "Means for recommending appropriate individuals based on analysis results" refers to a function that selects and recommends the most suitable person based on the analyzed user requirements.

[1392] "Means of obtaining schedules with recommended individuals" refers to the function of using schedule management software to obtain schedule information of recommended individuals.

[1393] "A means of finding a time that works for both the user and the recommended person" refers to a function that compares the schedules of the user and the recommended person to find available time for both of them.

[1394] The "automatic appointment scheduling based on available time" feature is a function that automatically schedules appointments based on the availability of both the user and the recommended person.

[1395] A description of embodiments for carrying out this invention will be given.

[1396] Users enter their appointment preferences in natural language using their device. For example, they can enter specific dates, times, and formats, such as "I'd like to schedule a one-on-one appointment for next Monday." This input is done through a means of entering the user's request in natural language.

[1397] The server receives input from the user and performs analysis using a generative AI model. This analysis utilizes natural language processing technology to convert the user's request into a specific appointment date, time, and format. A general-purpose natural language processing model can be used as the generative AI model. An example of a prompt is, "Please suggest the best appointment date and time based on the user's preferences."

[1398] Based on the analysis results, the server recommends a suitable person. To obtain the recommended person's schedule, the server uses scheduling software. Specifically, it uses common scheduling software such as the Google Calendar API to retrieve the schedule information of both the user and the recommended person.

[1399] Based on the acquired schedule information, the server finds a time that is convenient for both the user and the recommended person. To automatically set an appointment at the found time, the server again uses the schedule management software and adds the appointment to the calendar. This series of processes allows the user to set appointments efficiently. The flow of the specific process in Example 3 will be explained using Figure 15.

[1400] Step 1:

[1401] The user enters their appointment preferences in natural language using a terminal. For example, they might enter a specific date, time, and format, such as, "I'd like to schedule a one-on-one appointment for next Monday." This input forms the basis for the next processing step.

[1402] Step 2:

[1403] The server passes the natural language input received from the user to a generative AI model. The generative AI model uses prompts to analyze the user's request. Specifically, it analyzes the input natural language to identify the date, time, and format of the appointment. This analysis result becomes the input for the next step.

[1404] Step 3:

[1405] The server recommends a suitable person based on the analysis results. Information about the recommended person is retrieved from the database. The server searches the database using the analysis results and selects the most suitable person. This recommendation result becomes the input for the next step.

[1406] Step 4:

[1407] The server uses scheduling software to retrieve the schedules of recommended individuals. Specifically, it uses the Google Calendar API to obtain schedule information for both the user and the recommended individuals. This schedule information will then be used as input for the next step.

[1408] Step 5:

[1409] The server uses the retrieved schedule information to find a time that works for both the user and the recommended person. The server compares their availability and determines the optimal appointment date and time. This determined date and time becomes the input for the next step.

[1410] Step 6:

[1411] The server automatically sets appointments based on the time it finds. The server uses the Google Calendar API to add appointments to the calendar at the determined date and time. This eliminates the need for users to manually adjust their schedules.

[1412] (Application Example 3)

[1413] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1414] In modern organizations, efficiently scheduling appointments with the right person at the user's preferred date and time is crucial. However, traditional systems often require manual processes of checking the schedules of individuals within the organization based on the user's preferred date and time, and finding available time slots, which is time-consuming and laborious. Furthermore, the lack of functionality to automatically add confirmed appointments to the user's and the organization's personnel's calendars makes appointment management cumbersome.

[1415] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[1416] In this invention, the server includes means for inputting the user's experience and future goals; means for recommending appropriate individuals within the organization based on the relevant information; means for automatically setting appointments with the recommended individuals; means for inputting the user's desired date and time, checking...

Claims

[Claim 1] Equipped with a processor, The aforementioned processor, The system learns the characteristics of an employee from their output and registers these learned characteristics in a database. It provides an interface for users to input their experiences and future goals. The input information is analyzed using natural language processing to extract important keywords, and based on the extracted keywords and the characteristics registered in the database, a prompt is generated to instruct the generating AI model to perform the process of recommending an appropriate person to the user. The generated prompt is sent to the generating AI model, and the response is received. The system retrieves and compares the schedule information of the recommended person and the user included in the received response to identify their availability, and then uses a calendar API to automatically schedule appointments between the recommended person and the user during the identified availability. system.

Images