system

Abstract

We provide the system. [Solution] Means for receiving and collecting user input, Analysis means including artificial intelligence for analyzing collected user information, A plan proposal method that generates the optimal career plan for the user based on the analysis results, A means to present a generated career plan to the user and allow for customization, A support mechanism to provide additional advice in response to inquiries from users, A means of tracking progress information and generating feedback, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is 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 character of the chatbot, 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] As the era of 100-year life becomes a reality, the number of people who want to enrich their lives after retirement is increasing. However, securing funds for old age and exploring new careers that make use of their own experiences are accompanied by difficulties. It is not easy to find appropriate second career options for such problems. In order for people to pursue their hopes and dreams and lead a fulfilling life, it is required to provide an optimal second career plan according to individual needs and support its actual realization.

Means for Solving the Problems

[0005] This invention solves the above problem through a system that includes means for receiving input from the user, means for analyzing the user's conditions and desires using artificial intelligence based on the collected information, means for proposing a plan that generates an optimal career plan according to the analysis results, means for presenting the plan to the user and making it customizable, means for providing advice as needed, and means for tracking progress and providing feedback. As a result, the user can pursue concrete steps toward their desired career goals.

[0006] A "user" refers to an individual who uses the system to explore second career plans.

[0007] "Input" refers to the provision of data by users to convey their information and preferences to the system.

[0008] "Means of collection" refers to the function of receiving input data from users and compiling it appropriately.

[0009] "Artificial intelligence for information analysis" refers to machine learning technology that analyzes collected data to understand user conditions and preferences.

[0010] "Analysis methods" refer to the processes and technologies used to analyze user information using artificial intelligence.

[0011] "Plan proposal method" refers to a function that generates the optimal second career options for the user based on the analysis results.

[0012] "Presentation" refers to the act of visually or interactively showing the generated career plan to the user.

[0013] "Customization" refers to adjusting the presented plan to suit the user's specific needs and requirements.

[0014] "Support means" refers to the function of providing appropriate advice and information in response to users' consultations and questions.

[0015] "Progress information" refers to the data for recording the results of users' actions along the career plan.

[0016] "Feedback" refers to the information for supporting the next actions that users should take, such as improvement points and approval opinions provided based on the progress information.

Brief Explanation of Drawings

[0017] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12]It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0018] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a numbered processor (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 CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc.

[0021] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0022] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0023] 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).

[0024] 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."

[0025] [First Embodiment]

[0026] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0038] This invention relates to the realization of a support system that enables users living in the era of 100-year lifespans to achieve a fulfilling second career. The embodiments for carrying out this invention are described below.

[0039] The system begins with the user entering their work history, skills, and desired career details. The user does this through an interface on a terminal. The terminal receives the entered data and sends it to the server.

[0040] The server stores the received information in a database and analyzes the data using artificial intelligence. The AI ​​utilizes natural language processing and machine learning techniques to analyze user needs. This generates a second career plan tailored to the user's situation. This plan is optimized considering the user's experience, desires, and current social circumstances.

[0041] The generated plan is sent from the server to the terminal and presented to the user in a visual or interactive format. Users can then customize the presented plan to suit their own needs. As users customize, the system provides advice as needed, which may include access to additional information and learning resources related to their career plan.

[0042] Subsequently, as the user executes the plan, they periodically report their progress to the system via their terminal. The server generates feedback based on the reported progress information and provides guidance for the next steps. This allows the user to concretize the actions needed to achieve their goals and continuously improve.

[0043] For example, if a retired user expresses a desire to start an NPO, the system will consider the user's work history and volunteer experience and present a plan outlining the necessary skills, knowledge, and relevant organizations for NPO activities. The user can then customize the proposed plan and receive links and advice for learning the necessary skills through online courses.

[0044] In this way, the present invention provides concrete support for users to find and realize career plans that meet their individual needs.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The user logs into the career support system and accesses a form to enter their profile. The user enters their work history, skills, and desired career information, and then clicks the submit button.

[0048] Step 2:

[0049] The terminal receives the information entered by the user, formats it, and then sends the data to the server. It then verifies that the data has been successfully transmitted.

[0050] Step 3:

[0051] The server receives data from the terminal, saves it to a database, and launches an artificial intelligence analysis tool. Based on the saved data, the AI ​​analyzes the user's needs and preferences.

[0052] Step 4:

[0053] The server generates a career plan tailored to the user based on AI analysis results. It also provides related options and information for the generated plan.

[0054] Step 5:

[0055] The server generates a carrier plan and sends it to the terminal for display to the user. The plan is made visually verifiable on the user interface.

[0056] Step 6:

[0057] The user reviews the presented plan and considers the details. The user selects the items they want to customize and enters any necessary changes or additional information.

[0058] Step 7:

[0059] The device sends user customization information to the server. The server readjusts the plan based on the received information and generates an updated plan.

[0060] Step 8:

[0061] Based on the new plan determined by the server, AI is used to provide relevant advice and resource information to the user. The necessary information is then reflected in the user interface.

[0062] Step 9:

[0063] The user begins implementing their career plan and periodically records their progress via their device. The progress data is then updated and sent.

[0064] Step 10:

[0065] The server receives progress information, and the AI ​​analyzes this data to generate feedback and suggestions for the next steps. The generated feedback is then sent to the user.

[0066] (Example 1)

[0067] Next, we will describe 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."

[0068] In modern society, with increasing life expectancy, workers have a growing need to pursue diverse professional experiences and second career paths. However, there is insufficient concrete support for effectively utilizing individual experiences and skills and setting new career goals. Traditional vocational support systems lack the provision of flexible plans tailored to individual needs and continuous feedback based on progress, and this deficiency reduces the effectiveness of career changes.

[0069] 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.

[0070] In this invention, the server includes information receiving means, storage means, analysis means, planning means including a generative AI model, customization support means, support means, and progress information tracking and feedback means. This allows users to generate an optimized career plan based on their career history and skills, customize that plan, and receive feedback based on their progress. This enables career support tailored to individual needs and promotes effective career changes.

[0071] An "information receiving means" is a mechanism for receiving information about the user's background, skills, and desired occupation via a terminal to a server.

[0072] A "storage device" is a device that stores received user information in a storage device such as a database, making it available for later analysis and plan generation.

[0073] "Analysis methods" refer to techniques that use natural language processing and machine learning technologies to analyze stored user information and reveal user characteristics and needs.

[0074] A "generative AI model" is a generative algorithm or system that automatically creates a career plan optimized for the user based on analyzed information.

[0075] A "plan creation mechanism" is a system that uses generative AI models or similar tools to create and propose career plans to users.

[0076] "Customization support means" refers to a function that supports users in adjusting and modifying the generated career plan to suit their own needs.

[0077] "Support tools" refer to functions that provide access to necessary additional information and learning resources when customizing the plan.

[0078] "Progress tracking and feedback mechanisms" refer to a system that monitors the progress of users in executing their work plans and uses that information to provide suggestions for improvement and guidance for the next steps.

[0079] This invention begins with the user inputting their career history, skills, and desired occupation information. The user inputs this information via an interface on a terminal, and the terminal transmits this information to a server. The server stores the received information in a storage device and analyzes the data using analytical means. Here, natural language processing (NLP) and machine learning techniques are utilized to perform analysis in order to understand the user's characteristics and needs. The hardware used includes general-purpose computers and server systems, and the software includes NLP and machine learning libraries.

[0080] The server uses an AI model based on the analyzed information to create an optimal career plan for the user. In this planning process, an automatically generated plan is proposed to the user. The user can visually review this plan through the terminal interface and adjust the proposed career plan to their own needs using customization support tools. During customization, the support tools provide access to necessary additional information and learning resources.

[0081] During plan execution, users report progress information from their terminals to the server. The server uses progress tracking and feedback mechanisms to monitor the user's progress and provide feedback. This allows users to receive specific guidance for the next steps.

[0082] As a concrete example, consider a retired user who wishes to start a non-profit activity. In this case, the user's background and past volunteer work are taken into consideration, and a plan can be presented that includes the skills necessary for non-profit activities and information on relevant organizations. Furthermore, the user can customize the presented plan and receive links and advice to learn the necessary skills online. An example of a prompt would be, "Generate a plan for non-profit activities based on the user's work history, skills, and desired career details."

[0083] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0084] Step 1:

[0085] Users input their work history, skills, and desired occupation information through an interface on their device. This generates text data about their past jobs and specific skills. This input data is then sent to the server in the next step.

[0086] Step 2:

[0087] The terminal sends the information received from the user to the server as data packets. The server receives these packets and stores them in its storage device. At this point, all of the user's input information is stored in a structured format and is ready for later analysis.

[0088] Step 3:

[0089] The server processes the stored data using analytical tools. Specifically, it extracts keywords from text data using natural language processing (NLP) techniques, and machine learning algorithms analyze user characteristics and needs based on this information. The input data is converted into feature vectors that reflect the user's characteristics, and the results are output.

[0090] Step 4:

[0091] The server generates an optimal career plan for the user using an AI model based on the analysis results. This process is triggered by prompt messages, which cause the AI ​​model to output multiple career plans. The output plans are recommended plans selected based on the user's characteristics.

[0092] Step 5:

[0093] The server sends the generated job plan to the terminal. The user visually reviews the plan through the terminal's interface and adjusts it as needed using customization support tools. This process requires new data based on the user's customization choices as input, and the result is output as an updated plan.

[0094] Step 6:

[0095] Users execute a plan and periodically report their progress from their terminal to the server. The server tracks the progress information and generates and outputs feedback based on the progress data. Users use this feedback to obtain specific guidance for moving on to the next step.

[0096] (Application Example 1)

[0097] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0098] In an era of 100-year lifespans, individual citizens need personalized information and support to build new careers by appropriately utilizing their diverse backgrounds and skills, in order to achieve fulfilling second careers. However, in reality, there is a lack of systems that provide such personalized support, and in particular, support that effectively utilizes the resources of the entire city is not being provided. As a result, there is a challenge in that it is difficult for each citizen to find a suitable career plan and work towards achieving it.

[0099] 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.

[0100] In this invention, the server includes means for receiving and collecting user input, analysis means including artificial intelligence for analyzing the collected user information, and means for optimizing career plans by utilizing resources throughout the city. As a result, users can obtain an optimal career plan based on their own experience and skills, and by utilizing diverse resources within the city, the feasibility of the plan is increased, enabling a smooth transition to a second career.

[0101] "Means for receiving and collecting user input" refers to an interface for system users to input information such as their work history, skills, and career aspirations, as well as the technical means for appropriately collecting this information.

[0102] The "analysis method" is a processing system that uses artificial intelligence to analyze data based on collected user information and constructs the optimal career plan for each individual user.

[0103] The "plan proposal method" is a function that generates and presents the optimal second career plan for the user based on the analyzed information.

[0104] "Means of enabling customization" refers to technologies that allow users to adjust and modify a proposed career plan according to their own needs and conditions.

[0105] "Support tools" refer to features that provide additional advice and information when users consult about their plans.

[0106] "A means of optimizing career planning by utilizing resources throughout the city" refers to a system that enhances the feasibility of users' career plans by utilizing various resources available within the city, such as education, vocational training, and community programs.

[0107] "Means for tracking progress and providing feedback" refers to technologies that help users achieve their goals by tracking the progress of plans they have worked on and providing appropriate feedback.

[0108] To implement this invention, the user needs an electronic device, such as a smartphone or terminal. The user uses an application with an interface for inputting information about their background, skills, and career. This application is developed using Flutter® and is cross-platform compatible.

[0109] The terminal receives information entered by the user and sends it to the server. The server manages this information using the Django framework and analyzes the collected data using the scikit-learn library. Through this analysis, an optimal second career plan is generated. By optimizing the plan by considering the resources of the entire city relevant to the user, a more practical proposal becomes possible.

[0110] The generated career plan is sent to the device and presented to the user visually. The user can then customize the plan to suit their preferences and circumstances. Furthermore, the system's generating AI model operates in the background to provide additional advice and information, supporting the user in achieving their desired career path.

[0111] The server tracks the progress of plans implemented by users and provides necessary feedback. It also helps lower barriers to implementation by informing users about various resources within the city. Based on this feedback, users can continue their efforts towards achieving their goals.

[0112] For example, if a user expresses a desire to participate in local cultural activities, the system will incorporate local cultural organizations, events, and related learning resources into their career plan and suggest concrete steps toward participation. The following is an example of a prompt from this system.

[0113] Example prompt: "Based on your background and skills, I propose a plan for participation in the town's cultural activities. Specifically, you may consider engaging in the following activities..."

[0114] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0115] Step 1:

[0116] The user launches an application on their smartphone and enters information about their work history, skills, and career goals. The entered data is collected and temporarily stored through the interface on the device, and then prepared to be sent to the server.

[0117] Step 2:

[0118] The terminal sends the input data received from the user to the server. The data is sent in JSON format, and the server receives it using the Django framework and securely stores it in the database. This ensures the secure storage of user information.

[0119] Step 3:

[0120] The server analyzes the received user information using the scikit-learn library. This analysis involves pattern recognition and clustering based on the input data, laying the foundation for an optimal career plan for the user. The analysis results are then ready to be input into the generative AI model.

[0121] Step 4:

[0122] The server uses an AI model to generate an optimal career plan, taking into account user preferences and the resources of the entire city, based on analysis results obtained through machine learning. The output at this stage is an individualized career plan.

[0123] Step 5:

[0124] The generated carrier plan is sent from the server to the device and visually presented to the user via the application. The user is then shown options to customize the plan, allowing them to adjust it to suit their own needs.

[0125] Step 6:

[0126] When a user takes action towards completing a career, the device periodically reports progress information to the server. Based on this information, the server generates feedback and provides advice for the next steps.

[0127] Step 7:

[0128] As support throughout the process, the server continuously provides suggestions and advice to the user using example prompts and related information. These prompts are dynamically generated using a generative AI model and provided to the user in a specific form, such as, "Based on your background and skills, we propose a plan for participating in local cultural activities."

[0129] 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.

[0130] This invention relates to a system that provides support tailored to the individual needs of users as they pursue a second career. In particular, it achieves more accurate support by using an emotion engine that recognizes and considers the user's emotions.

[0131] The system begins with the user entering information about their career. The user inputs information about their work history, current feelings, and desired career vision via a device. At this stage, the device activates an emotion engine that analyzes the user's emotions behind the entered information.

[0132] The analyzed emotional information is sent to a server and comprehensively analyzed by artificial intelligence in conjunction with the user's career aspirations. Based on this analysis, the server generates a career plan that takes the user's emotions into consideration. For example, if a user feels anxious about a particular work environment, the system will suggest an approach that reflects those emotions and recommend appropriate resources and support.

[0133] The generated plan is presented to the user via their device, and the user can customize it to reflect their emotions. Furthermore, when the user requests advice, the emotion engine reactivates to provide advice that reflects the user's current feelings. Through this process, the realization of a second career that meets the user's emotional needs is supported.

[0134] Furthermore, after users begin implementing their career plan, they can periodically report their progress via their device. This progress information is sent to the server, where the emotion engine re-evaluates the user's emotional state. The server uses this information to optimize feedback and help users effectively progress towards their desired career goals.

[0135] For example, if a user is aiming to become an independent freelance consultant, and the emotion engine detects "anxiety and anticipation" at the time of input, the system will also provide information on risk management courses and mental support that correspond to those emotions. In this way, an environment is created where users can take new steps with a more personalized plan, while also considering emotional aspects.

[0136] The following describes the processing flow.

[0137] Step 1:

[0138] The user accesses their device and logs into the career support system. The user fills out a form with details about their work history, skills, and desired second career.

[0139] Step 2:

[0140] The terminal receives user input and activates an emotion engine to recognize the emotions contained in it. The emotion engine analyzes the input data and identifies the user's emotional state.

[0141] Step 3:

[0142] The device sends input information and associated emotional information to the server. Upon receiving the data, the server stores it in a database and begins a comprehensive data analysis using an AI analysis tool.

[0143] Step 4:

[0144] The server analyzes the user's information and emotional state to generate a career plan tailored to the user. The generated plan incorporates elements that take the user's emotions into consideration.

[0145] Step 5:

[0146] The server sends a generated carrier plan to the terminal and presents it visually to the user. The user can review the plan and customize it to suit their needs.

[0147] Step 6:

[0148] Users can review the plan and make customizations related to specific emotions. If the user enters additional information, the device sends it back to the server.

[0149] Step 7:

[0150] The server receives updated information, re-evaluates the plan, and fine-tunes the approach. If necessary, the emotion engine generates emotional feedback and provides advice to the user.

[0151] Step 8:

[0152] The user begins executing the plan, recording and reporting progress via their device. The device then sends this progress data to the server.

[0153] Step 9:

[0154] The server analyzes progress information and uses an emotion engine to evaluate the user's emotional state. Based on the analysis results, it generates feedback and sends a next action plan to the user.

[0155] (Example 2)

[0156] Next, we will describe 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".

[0157] In today's world, it is difficult for individual users to effectively develop career plans that take their own emotions into account. This problem stems from a lack of detailed support to help users achieve their desired careers. Furthermore, the lack of emotion-based planning makes it difficult to alleviate user anxiety and stress during the career selection process. To solve these challenges, a system is needed that can recognize users' individual needs at an emotional level and propose optimized career plans.

[0158] 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.

[0159] In this invention, the server includes emotion analysis means for analyzing the user's emotional information and extracting the underlying emotions; analysis means for comprehensively analyzing the transmitted emotional information and career aspirations to generate an optimal career plan for the user; and feedback generation means for optimizing feedback based on the emotional information and providing it to the user. This enables users to develop career plans that take their individual emotions into account, reducing anxiety about career choices and enabling them to effectively achieve their career goals.

[0160] A "user" refers to an individual who intends to use this system to develop a career plan.

[0161] A "terminal" refers to an electronic device used by a user to input information or view generated carrier plans.

[0162] "Work history" refers to information about the occupations and work experience a user has held up to date.

[0163] "Feelings" refers to the user's current emotions and psychological state.

[0164] "Career vision" refers to the professional goals and visions that a user hopes to achieve in the future.

[0165] "Emotional analysis methods" refer to technologies and methods for extracting the underlying emotions based on information entered by the user.

[0166] "Information transfer means" refers to the technology and processes used to transmit analyzed emotional information to a server.

[0167] "Analysis means" refers to the technology within the system that comprehensively analyzes the user's emotional information and career aspirations to generate the optimal career plan.

[0168] "Plan presentation method" refers to the interface or technology used to display the generated career plan to the user and allow for customization.

[0169] "Re-evaluation methods" refer to technologies for re-evaluating a user's emotional state based on their progress information.

[0170] "Feedback generation means" refers to technologies and processes for generating feedback to be provided to users based on emotional information.

[0171] To implement this invention, the following means are used. First, the user inputs their work history, feelings, and desired career vision using a terminal. The terminal provides a user interface that makes it easy for the user to operate while collecting this information.

[0172] Subsequently, the device uses emotion analysis tools to analyze the user's input information and extract the underlying emotions. Natural Language Processing (NLP) technology is used for this emotion analysis. For example, emotional states such as "anxiety" and "expectation" are tagged.

[0173] The analyzed emotional information is encrypted by the information transfer method and sent to the server via a secure protocol. The server uses an artificial intelligence model as an analysis tool to comprehensively analyze the user's emotional information and career aspirations and generate an optimal career plan. This analysis process involves machine learning algorithms and inference based on similar past cases.

[0174] The generated career plan is presented to the user on their device using a plan presentation tool. Users can customize this plan, adjusting it to their liking using drag-and-drop or direct editing functions.

[0175] Furthermore, when a user begins taking action based on a generated plan, a re-evaluation mechanism is periodically activated to re-evaluate their emotional state based on progress information. Based on this information, the server uses a feedback generation mechanism to provide optimized feedback to the user.

[0176] As a concrete example, consider a case where a user is a freelance consultant who wants to become independent. If this user consults about feelings such as "anxiety and excitement," the system will suggest risk management courses and mental support information specifically tailored to these emotions.

[0177] An example of a prompt generated using an AI model might be: "I'm feeling anxious about my career as a freelance consultant. How can I alleviate my anxiety and move on to the next step?" This prompt allows the AI ​​to provide the user with appropriate advice and resources.

[0178] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0179] Step 1:

[0180] The user uses the terminal to input their work history, current feelings, and desired career vision. The entered data is imported into the terminal via the user interface. The terminal displays a guide to help the user input all the necessary information without omission.

[0181] Step 2:

[0182] The terminal activates an emotion analysis system based on the input data. This system uses Natural Language Processing (NLP) technology to analyze the text data and extract emotion tags. For example, emotions such as "anxiety" and "anticipation" may be detected. The analysis results are output as numerical values ​​or tags representing the user's emotional state.

[0183] Step 3:

[0184] The terminal transmits the extracted sentiment information and user input data to the server using an information transfer method. During this process, the data is encrypted using a secure protocol. The server receives this encrypted data and converts the data structure into a format suitable for analysis.

[0185] Step 4:

[0186] The server performs a comprehensive analysis using analytical tools based on the received data. Specifically, it uses a generative AI model and machine learning algorithms to analyze the user's emotions and career aspirations. The server searches a database of similar cases and performs pattern recognition to generate the optimal career plan. Through this process, a career plan tailored to the user is output.

[0187] Step 5:

[0188] The generated career plan is sent from the server to the device. The device uses a plan presentation tool to visually display this plan to the user. The user can review the plan's contents and customize it to their own feelings and goals through drag-and-drop or direct editing.

[0189] Step 6:

[0190] After the user begins executing their career plan, the device collects progress information and sends it to the server. The server periodically activates a re-evaluation mechanism to reassess the emotional state based on the progress information. Based on this analysis, the server generates any necessary feedback.

[0191] Step 7:

[0192] The re-evaluation results and optimized feedback are sent to the device using a feedback generation mechanism. The device presents the feedback to the user, allowing them to further adjust their actions on the spot. This entire process enables the user to engage in continuous career planning that takes their own emotions into account.

[0193] (Application Example 2)

[0194] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0195] In modern society, when citizens venture into new professions or fields, they require specific support tailored to their individual emotions and needs. However, current systems lack sufficient support that adequately considers users' emotions, making it difficult to provide comprehensive and flexible career plans. Therefore, the challenge lies in accurately understanding users' emotions and providing the most appropriate resources and approaches accordingly.

[0196] 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.

[0197] In this invention, the server includes a device for receiving and collecting user input, an automated analysis device for analyzing the collected user information, and a device for considering the analyzed emotional information and presenting the user with resources that correspond to their emotions. This makes it possible to provide a flexible and personalized career plan that takes the user's emotions into consideration.

[0198] A "device that receives and collects user input" is equipment that acquires occupation-related information and emotional data from users and stores it within the system.

[0199] An "automated analysis device" is a piece of equipment that uses artificial intelligence to analyze collected user information and evaluate emotions and occupational needs.

[0200] A "proposal device" is equipment that generates and presents an optimal career plan to the user based on the analysis results.

[0201] A "device that presents a generated occupational plan to the user and allows for modifications" is equipment that displays the generated occupational plan to the user and provides the function to modify or customize it.

[0202] A "support device" is equipment designed to provide appropriate advice and resources in response to additional inquiries from users.

[0203] A "feedback generating device" is equipment that collects user career progress information and generates appropriate opinions based on changes in their emotional state.

[0204] A "device that presents resources according to emotions" is equipment that provides useful resources and support appropriate to the user's situation, based on their analyzed emotions.

[0205] This system receives career-related information from users and provides personalized career plans. Information entered through the user's terminal primarily includes work history, feelings, and career vision. This information is collected by a terminal with emotion recognition capabilities, which activates an emotion engine to analyze the user's emotions. The software used at this stage includes the "transformers" (Hugging Face) library for natural language processing.

[0206] The server uses analyzed emotional and career information to generate a comprehensive career plan, leveraging artificial intelligence. This process suggests the most suitable resources and support tools to the user based on the emotional analysis results. For example, if the analysis reveals the user is experiencing anxiety in a new field, the server will recommend risk management and mental support courses.

[0207] Users can review the career plan presented through their device and customize it based on their emotions. Regular progress reports provide feedback and advice tailored to their emotional state. Throughout this process, the server adjusts the plan based on the feedback, continuously supporting the user in achieving their goals.

[0208] For example, if a user wants to build a career in a new technology field, they might input thoughts like, "I'm excited about learning the technology, but I'm also a little anxious." In this case, the server uses an emotion engine to recognize the user's "expectations and anxieties" and proposes a technology training program or mental support sessions.

[0209] Examples of prompts include, "Analyze the sentiment of the following text: 'I'm excited to learn technology, but I'm also a little anxious.'" and "The user is feeling anxious. Generate a career plan that addresses this." This enables the creation of flexible and effective career plans that take into account the individual emotional state of each user.

[0210] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0211] Step 1:

[0212] The user inputs information about their work history, feelings, and career vision through their device. The input information is temporarily stored on the device, and the emotion engine is activated. The emotion engine analyzes the input text using natural language processing technology and extracts the user's emotions as numerical data. The input is text data, and the output is an emotion score.

[0213] Step 2:

[0214] The terminal sends user data, along with analyzed sentiment information, to the server. Based on the received data, the server uses an analysis algorithm to evaluate the user's occupational needs. Here, the input is user data and sentiment score, and the output is the user's career needs evaluation data.

[0215] Step 3:

[0216] The server generates an optimal career plan using a generative AI model based on sentiment scores and career needs assessments. In this process, the AI ​​consults a large database to select resources and services suitable for the user. The input is career needs assessment data, and the output is career plan data.

[0217] Step 4:

[0218] The generated career plan is sent to the terminal and presented to the user. The user can review the presented career plan and customize it through the user interface. The input is the career plan data, and the output is the customized plan data from the user.

[0219] Step 5:

[0220] After the user begins taking action based on their career plan, the device periodically collects progress data and records any associated changes in their mood. This data is then sent back to the server and used to generate feedback. The input is progress and mood data, and the output is feedback data.

[0221] Step 6:

[0222] The server takes the new feedback into account and evaluates whether the user's career plan needs to be updated. If necessary, it modifies the career plan and sends it back to the terminal. The final output is the updated career plan.

[0223] 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.

[0224] Data generation model 58 is a 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> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">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.

[0225] 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.

[0226] [Second Embodiment]

[0227] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0228] 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.

[0229] 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).

[0230] 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.

[0231] 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.

[0232] 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).

[0233] 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.

[0234] 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.

[0235] 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.

[0236] 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.

[0237] 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.

[0238] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0239] This invention relates to the realization of a support system that enables users living in the era of 100-year lifespans to achieve a fulfilling second career. The embodiments for carrying out this invention are described below.

[0240] The system begins with the user entering their work history, skills, and desired career details. The user does this through an interface on a terminal. The terminal receives the entered data and sends it to the server.

[0241] The server stores the received information in a database and analyzes the data using artificial intelligence. The AI ​​utilizes natural language processing and machine learning techniques to analyze user needs. This generates a second career plan tailored to the user's situation. This plan is optimized considering the user's experience, desires, and current social circumstances.

[0242] The generated plan is sent from the server to the terminal and presented to the user in a visual or interactive format. Users can then customize the presented plan to suit their own needs. As users customize, the system provides advice as needed, which may include access to additional information and learning resources related to their career plan.

[0243] Subsequently, as the user executes the plan, they periodically report their progress to the system via their terminal. The server generates feedback based on the reported progress information and provides guidance for the next steps. This allows the user to concretize the actions needed to achieve their goals and continuously improve.

[0244] For example, if a retired user expresses a desire to start an NPO, the system will consider the user's work history and volunteer experience and present a plan outlining the necessary skills, knowledge, and relevant organizations for NPO activities. The user can then customize the proposed plan and receive links and advice for learning the necessary skills through online courses.

[0245] In this way, the present invention provides concrete support for users to find and realize career plans that meet their individual needs.

[0246] The following describes the processing flow.

[0247] Step 1:

[0248] The user logs into the career support system and accesses a form to enter their profile. The user enters their work history, skills, and desired career information, and then clicks the submit button.

[0249] Step 2:

[0250] The terminal receives the information entered by the user, formats it, and then sends the data to the server. It then verifies that the data has been successfully transmitted.

[0251] Step 3:

[0252] The server receives data from the terminal, saves it to a database, and launches an artificial intelligence analysis tool. Based on the saved data, the AI ​​analyzes the user's needs and preferences.

[0253] Step 4:

[0254] The server generates a career plan tailored to the user based on AI analysis results. It also provides related options and information for the generated plan.

[0255] Step 5:

[0256] The server generates a carrier plan and sends it to the terminal for display to the user. The plan is made visually verifiable on the user interface.

[0257] Step 6:

[0258] The user reviews the presented plan and considers the details. The user selects the items they want to customize and enters any necessary changes or additional information.

[0259] Step 7:

[0260] The device sends user customization information to the server. The server readjusts the plan based on the received information and generates an updated plan.

[0261] Step 8:

[0262] Based on the new plan determined by the server, AI is used to provide relevant advice and resource information to the user. The necessary information is then reflected in the user interface.

[0263] Step 9:

[0264] The user begins implementing their career plan and periodically records their progress via their device. The progress data is then updated and sent.

[0265] Step 10:

[0266] The server receives progress information, and the AI ​​analyzes this data to generate feedback and suggestions for the next steps. The generated feedback is then sent to the user.

[0267] (Example 1)

[0268] Next, we will describe 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."

[0269] In modern society, with increasing life expectancy, workers have a growing need to pursue diverse professional experiences and second career paths. However, there is insufficient concrete support for effectively utilizing individual experiences and skills and setting new career goals. Traditional vocational support systems lack the provision of flexible plans tailored to individual needs and continuous feedback based on progress, and this deficiency reduces the effectiveness of career changes.

[0270] 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.

[0271] In this invention, the server includes information receiving means, storage means, analysis means, planning means including a generative AI model, customization support means, support means, and progress information tracking and feedback means. This allows users to generate an optimized career plan based on their career history and skills, customize that plan, and receive feedback based on their progress. This enables career support tailored to individual needs and promotes effective career changes.

[0272] An "information receiving means" is a mechanism for receiving information about the user's background, skills, and desired occupation via a terminal to a server.

[0273] A "storage device" is a device that stores received user information in a storage device such as a database, making it available for later analysis and plan generation.

[0274] "Analysis methods" refer to techniques that use natural language processing and machine learning technologies to analyze stored user information and reveal user characteristics and needs.

[0275] A "generative AI model" is a generative algorithm or system that automatically creates a career plan optimized for the user based on analyzed information.

[0276] A "plan creation mechanism" is a system that uses generative AI models or similar tools to create and propose career plans to users.

[0277] "Customization support means" refers to a function that supports users in adjusting and modifying the generated career plan to suit their own needs.

[0278] "Support tools" refer to functions that provide access to necessary additional information and learning resources when customizing the plan.

[0279] "Progress tracking and feedback mechanisms" refer to a system that monitors the progress of users in executing their work plans and uses that information to provide suggestions for improvement and guidance for the next steps.

[0280] This invention begins with the user inputting their career history, skills, and desired occupation information. The user inputs this information via an interface on a terminal, and the terminal transmits this information to a server. The server stores the received information in a storage device and analyzes the data using analytical means. Here, natural language processing (NLP) and machine learning techniques are utilized to perform analysis in order to understand the user's characteristics and needs. The hardware used includes general-purpose computers and server systems, and the software includes NLP and machine learning libraries.

[0281] The server uses an AI model based on the analyzed information to create an optimal career plan for the user. In this planning process, an automatically generated plan is proposed to the user. The user can visually review this plan through the terminal interface and adjust the proposed career plan to their own needs using customization support tools. During customization, the support tools provide access to necessary additional information and learning resources.

[0282] During plan execution, users report progress information from their terminals to the server. The server uses progress tracking and feedback mechanisms to monitor the user's progress and provide feedback. This allows users to receive specific guidance for the next steps.

[0283] As a specific example, consider the case where a retired user wishes to "start a non-profit activity". In this case, the user's history and past volunteer activities are considered, and information on the skills required for non-profit activities and related organizations can be presented as a plan. Furthermore, the user can customize the presented plan and receive links and advice for online learning of the skills required for implementation. Examples of prompt sentences include "Please generate a plan for non-profit activities based on the user's job history, skills, and desired career details."

[0284] The flow of the specific process in Example 1 will be described using FIG. 11.

[0285] Step 1:

[0286] The user inputs their history, skills, and desired career information through the interface on the terminal. As a result, the user generates text data about their past jobs and specific skills. This input data serves as the material to be sent to the server in the next step.

[0287] Step 2:

[0288] The terminal sends the information received from the user to the server as data packets. The server receives this and stores it in the storage device. At this point, all the input information of the user is stored in a structured format and is ready to be used for later analysis.

[0289] Step 3:

[0290] The server processes the stored data using analysis means. Specifically, natural language processing (NLP) technology is used to extract keywords from the text data, and machine learning algorithms analyze the user's characteristics and needs based on this information. The input data is converted into a feature vector reflecting the user's characteristics, and the result is output.

[0291] Step 4:

[0292] The server generates an optimal career plan for the user using an AI model based on the analysis results. This process is triggered by prompt messages, which cause the AI ​​model to output multiple career plans. The output plans are recommended plans selected based on the user's characteristics.

[0293] Step 5:

[0294] The server sends the generated job plan to the terminal. The user visually reviews the plan through the terminal's interface and adjusts it as needed using customization support tools. This process requires new data based on the user's customization choices as input, and the result is output as an updated plan.

[0295] Step 6:

[0296] Users execute a plan and periodically report their progress from their terminal to the server. The server tracks the progress information and generates and outputs feedback based on the progress data. Users use this feedback to obtain specific guidance for moving on to the next step.

[0297] (Application Example 1)

[0298] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0299] In an era of 100-year lifespans, individual citizens need personalized information and support to build new careers by appropriately utilizing their diverse backgrounds and skills, in order to achieve fulfilling second careers. However, in reality, there is a lack of systems that provide such personalized support, and in particular, support that effectively utilizes the resources of the entire city is not being provided. As a result, there is a challenge in that it is difficult for each citizen to find a suitable career plan and work towards achieving it.

[0300] 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.

[0301] In this invention, the server includes means for receiving and collecting user input, analysis means including artificial intelligence for analyzing the collected user information, and means for optimizing career plans by utilizing resources throughout the city. As a result, users can obtain an optimal career plan based on their own experience and skills, and by utilizing diverse resources within the city, the feasibility of the plan is increased, enabling a smooth transition to a second career.

[0302] "Means for receiving and collecting user input" refers to an interface for system users to input information such as their work history, skills, and career aspirations, as well as the technical means for appropriately collecting this information.

[0303] The "analysis method" is a processing system that uses artificial intelligence to analyze data based on collected user information and constructs the optimal career plan for each individual user.

[0304] The "plan proposal method" is a function that generates and presents the optimal second career plan for the user based on the analyzed information.

[0305] "Means of enabling customization" refers to technologies that allow users to adjust and modify a proposed career plan according to their own needs and conditions.

[0306] "Support tools" refer to features that provide additional advice and information when users consult about their plans.

[0307] The means of "optimizing career plans by utilizing the resources of the entire city" is a system that uses various resources such as education, vocational training, and community programs existing within the city to enhance the feasibility of users' career plans.

[0308] The means of "tracking progress information and providing feedback" is a technology that supports users in achieving their goals by tracking the progress of the plans they are working on and providing appropriate feedback.

[0309] To implement this invention, an electronic device owned by the user, namely a smartphone or a terminal, is required. The user uses an application that has an interface for inputting information regarding their history, skills, and career. This application is developed using Flutter and realizes cross-platform compatibility.

[0310] The terminal receives the information input by the user and transmits it to the server. The server manages the information using the Django framework and analyzes the collected data using the scikit-learn library. Through the analysis, an optimal second career plan is generated. By optimizing the plan considering the resources of the entire city related to the user, more practical proposals become possible.

[0311] The generated career plan is transmitted to the terminal and visually presented to the user. At this time, the user can customize the plan according to their wishes and conditions. Furthermore, for the system to provide additional advice and information, a generative AI model operates in the background to support the realization of the specific career the user seeks.

[0312] The server tracks the progress of plans implemented by users and provides necessary feedback. It also helps lower barriers to implementation by informing users about various resources within the city. Based on this feedback, users can continue their efforts towards achieving their goals.

[0313] For example, if a user expresses a desire to participate in local cultural activities, the system will incorporate local cultural organizations, events, and related learning resources into their career plan and suggest concrete steps toward participation. The following is an example of a prompt from this system.

[0314] Example prompt: "Based on your background and skills, I propose a plan for participation in the town's cultural activities. Specifically, you may consider engaging in the following activities..."

[0315] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0316] Step 1:

[0317] The user launches an application on their smartphone and enters information about their work history, skills, and career goals. The entered data is collected and temporarily stored through the interface on the device, and then prepared to be sent to the server.

[0318] Step 2:

[0319] The terminal sends the input data received from the user to the server. The data is sent in JSON format, and the server receives it using the Django framework and securely stores it in the database. This ensures the secure storage of user information.

[0320] Step 3:

[0321] The server analyzes the received user information using the scikit-learn library. This analysis involves pattern recognition and clustering based on the input data, laying the foundation for an optimal career plan for the user. The analysis results are then ready to be input into the generative AI model.

[0322] Step 4:

[0323] The server uses an AI model to generate an optimal career plan, taking into account user preferences and the resources of the entire city, based on analysis results obtained through machine learning. The output at this stage is an individualized career plan.

[0324] Step 5:

[0325] The generated carrier plan is sent from the server to the device and visually presented to the user via the application. The user is then shown options to customize the plan, allowing them to adjust it to suit their own needs.

[0326] Step 6:

[0327] When a user takes action towards completing a career, the device periodically reports progress information to the server. Based on this information, the server generates feedback and provides advice for the next steps.

[0328] Step 7:

[0329] As support throughout the process, the server continuously provides suggestions and advice to the user using example prompts and related information. These prompts are dynamically generated using a generative AI model and provided to the user in a specific form, such as, "Based on your background and skills, we propose a plan for participating in local cultural activities."

[0330] 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.

[0331] This invention relates to a system that provides support tailored to the individual needs of users as they pursue a second career. In particular, it achieves more accurate support by using an emotion engine that recognizes and considers the user's emotions.

[0332] The system begins with the user entering information about their career. The user inputs information about their work history, current feelings, and desired career vision via a device. At this stage, the device activates an emotion engine that analyzes the user's emotions behind the entered information.

[0333] The analyzed emotional information is sent to a server and comprehensively analyzed by artificial intelligence in conjunction with the user's career aspirations. Based on this analysis, the server generates a career plan that takes the user's emotions into consideration. For example, if a user feels anxious about a particular work environment, the system will suggest an approach that reflects those emotions and recommend appropriate resources and support.

[0334] The generated plan is presented to the user via their device, and the user can customize it to reflect their emotions. Furthermore, when the user requests advice, the emotion engine reactivates to provide advice that reflects the user's current feelings. Through this process, the realization of a second career that meets the user's emotional needs is supported.

[0335] Furthermore, after users begin implementing their career plan, they can periodically report their progress via their device. This progress information is sent to the server, where the emotion engine re-evaluates the user's emotional state. The server uses this information to optimize feedback and help users effectively progress towards their desired career goals.

[0336] For example, if a user is aiming to become an independent freelance consultant, and the emotion engine detects "anxiety and anticipation" at the time of input, the system will also provide information on risk management courses and mental support that correspond to those emotions. In this way, an environment is created where users can take new steps with a more personalized plan, while also considering emotional aspects.

[0337] The following describes the processing flow.

[0338] Step 1:

[0339] The user accesses their device and logs into the career support system. The user fills out a form with details about their work history, skills, and desired second career.

[0340] Step 2:

[0341] The terminal receives user input and activates an emotion engine to recognize the emotions contained in it. The emotion engine analyzes the input data and identifies the user's emotional state.

[0342] Step 3:

[0343] The device sends input information and associated emotional information to the server. Upon receiving the data, the server stores it in a database and begins a comprehensive data analysis using an AI analysis tool.

[0344] Step 4:

[0345] The server analyzes the user's information and emotional state to generate a career plan tailored to the user. The generated plan incorporates elements that take the user's emotions into consideration.

[0346] Step 5:

[0347] The server sends a generated carrier plan to the terminal and presents it visually to the user. The user can review the plan and customize it to suit their needs.

[0348] Step 6:

[0349] Users can review the plan and make customizations related to specific emotions. If the user enters additional information, the device sends it back to the server.

[0350] Step 7:

[0351] The server receives updated information, re-evaluates the plan, and fine-tunes the approach. If necessary, the emotion engine generates emotional feedback and provides advice to the user.

[0352] Step 8:

[0353] The user begins executing the plan, recording and reporting progress via their device. The device then sends this progress data to the server.

[0354] Step 9:

[0355] The server analyzes progress information and uses an emotion engine to evaluate the user's emotional state. Based on the analysis results, it generates feedback and sends a next action plan to the user.

[0356] (Example 2)

[0357] Next, we will describe 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".

[0358] In today's world, it is difficult for individual users to effectively develop career plans that take their own emotions into account. This problem stems from a lack of detailed support to help users achieve their desired careers. Furthermore, the lack of emotion-based planning makes it difficult to alleviate user anxiety and stress during the career selection process. To solve these challenges, a system is needed that can recognize users' individual needs at an emotional level and propose optimized career plans.

[0359] 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.

[0360] In this invention, the server includes emotion analysis means for analyzing the user's emotional information and extracting the underlying emotions; analysis means for comprehensively analyzing the transmitted emotional information and career aspirations to generate an optimal career plan for the user; and feedback generation means for optimizing feedback based on the emotional information and providing it to the user. This enables users to develop career plans that take their individual emotions into account, reducing anxiety about career choices and enabling them to effectively achieve their career goals.

[0361] A "user" refers to an individual who intends to use this system to develop a career plan.

[0362] A "terminal" refers to an electronic device used by a user to input information or view generated carrier plans.

[0363] "Work history" refers to information about the occupations and work experience a user has held up to date.

[0364] "Feelings" refers to the user's current emotions and psychological state.

[0365] "Career vision" refers to the professional goals and visions that a user hopes to achieve in the future.

[0366] "Emotional analysis methods" refer to technologies and methods for extracting the underlying emotions based on information entered by the user.

[0367] "Information transfer means" refers to the technology and processes used to transmit analyzed emotional information to a server.

[0368] "Analysis means" refers to the technology within the system that comprehensively analyzes the user's emotional information and career aspirations to generate the optimal career plan.

[0369] "Plan presentation method" refers to the interface or technology used to display the generated career plan to the user and allow for customization.

[0370] "Re-evaluation methods" refer to technologies for re-evaluating a user's emotional state based on their progress information.

[0371] "Feedback generation means" refers to technologies and processes for generating feedback to be provided to users based on emotional information.

[0372] To implement this invention, the following means are used. First, the user inputs their work history, feelings, and desired career vision using a terminal. The terminal provides a user interface that makes it easy for the user to operate while collecting this information.

[0373] Subsequently, the device uses emotion analysis tools to analyze the user's input information and extract the underlying emotions. Natural Language Processing (NLP) technology is used for this emotion analysis. For example, emotional states such as "anxiety" and "expectation" are tagged.

[0374] The analyzed emotional information is encrypted by the information transfer method and sent to the server via a secure protocol. The server uses an artificial intelligence model as an analysis tool to comprehensively analyze the user's emotional information and career aspirations and generate an optimal career plan. This analysis process involves machine learning algorithms and inference based on similar past cases.

[0375] The generated career plan is presented to the user on their device using a plan presentation tool. Users can customize this plan, adjusting it to their liking using drag-and-drop or direct editing functions.

[0376] Furthermore, when a user begins taking action based on a generated plan, a re-evaluation mechanism is periodically activated to re-evaluate their emotional state based on progress information. Based on this information, the server uses a feedback generation mechanism to provide optimized feedback to the user.

[0377] As a concrete example, consider a case where a user is a freelance consultant who wants to become independent. If this user consults about feelings such as "anxiety and excitement," the system will suggest risk management courses and mental support information specifically tailored to these emotions.

[0378] An example of a prompt generated using an AI model might be: "I'm feeling anxious about my career as a freelance consultant. How can I alleviate my anxiety and move on to the next step?" This prompt allows the AI ​​to provide the user with appropriate advice and resources.

[0379] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0380] Step 1:

[0381] The user uses the terminal to input their work history, current feelings, and desired career vision. The entered data is imported into the terminal via the user interface. The terminal displays a guide to help the user input all the necessary information without omission.

[0382] Step 2:

[0383] The terminal activates an emotion analysis system based on the input data. This system uses Natural Language Processing (NLP) technology to analyze the text data and extract emotion tags. For example, emotions such as "anxiety" and "anticipation" may be detected. The analysis results are output as numerical values ​​or tags representing the user's emotional state.

[0384] Step 3:

[0385] The terminal transmits the extracted sentiment information and user input data to the server using an information transfer method. During this process, the data is encrypted using a secure protocol. The server receives this encrypted data and converts the data structure into a format suitable for analysis.

[0386] Step 4:

[0387] The server performs a comprehensive analysis using analytical tools based on the received data. Specifically, it uses a generative AI model and machine learning algorithms to analyze the user's emotions and career aspirations. The server searches a database of similar cases and performs pattern recognition to generate the optimal career plan. Through this process, a career plan tailored to the user is output.

[0388] Step 5:

[0389] The generated career plan is sent from the server to the device. The device uses a plan presentation tool to visually display this plan to the user. The user can review the plan's contents and customize it to their own feelings and goals through drag-and-drop or direct editing.

[0390] Step 6:

[0391] After the user begins executing their career plan, the device collects progress information and sends it to the server. The server periodically activates a re-evaluation mechanism to reassess the emotional state based on the progress information. Based on this analysis, the server generates any necessary feedback.

[0392] Step 7:

[0393] The re-evaluation results and optimized feedback are sent to the device using a feedback generation mechanism. The device presents the feedback to the user, allowing them to further adjust their actions on the spot. This entire process enables the user to engage in continuous career planning that takes their own emotions into account.

[0394] (Application Example 2)

[0395] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0396] In modern society, when citizens venture into new professions or fields, they require specific support tailored to their individual emotions and needs. However, current systems lack sufficient support that adequately considers users' emotions, making it difficult to provide comprehensive and flexible career plans. Therefore, the challenge lies in accurately understanding users' emotions and providing the most appropriate resources and approaches accordingly.

[0397] 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.

[0398] In this invention, the server includes a device for receiving and collecting user input, an automated analysis device for analyzing the collected user information, and a device for considering the analyzed emotional information and presenting the user with resources that correspond to their emotions. This makes it possible to provide a flexible and personalized career plan that takes the user's emotions into consideration.

[0399] A "device that receives and collects user input" is equipment that acquires occupation-related information and emotional data from users and stores it within the system.

[0400] An "automated analysis device" is a piece of equipment that uses artificial intelligence to analyze collected user information and evaluate emotions and occupational needs.

[0401] A "proposal device" is equipment that generates and presents an optimal career plan to the user based on the analysis results.

[0402] A "device that presents a generated occupational plan to the user and allows for modifications" is equipment that displays the generated occupational plan to the user and provides the function to modify or customize it.

[0403] A "support device" is equipment designed to provide appropriate advice and resources in response to additional inquiries from users.

[0404] A "feedback generating device" is equipment that collects user career progress information and generates appropriate opinions based on changes in their emotional state.

[0405] A "device that presents resources according to emotions" is equipment that provides useful resources and support appropriate to the user's situation, based on their analyzed emotions.

[0406] This system receives career-related information from users and provides personalized career plans. Information entered through the user's terminal primarily includes work history, feelings, and career vision. This information is collected by a terminal with emotion recognition capabilities, which activates an emotion engine to analyze the user's emotions. The software used at this stage includes the "transformers" (Hugging Face) library for natural language processing.

[0407] The server uses analyzed emotional and career information to generate a comprehensive career plan, leveraging artificial intelligence. This process suggests the most suitable resources and support tools to the user based on the emotional analysis results. For example, if the analysis reveals the user is experiencing anxiety in a new field, the server will recommend risk management and mental support courses.

[0408] Users can review the career plan presented through their device and customize it based on their emotions. Regular progress reports provide feedback and advice tailored to their emotional state. Throughout this process, the server adjusts the plan based on the feedback, continuously supporting the user in achieving their goals.

[0409] For example, if a user wants to build a career in a new technology field, they might input thoughts like, "I'm excited about learning the technology, but I'm also a little anxious." In this case, the server uses an emotion engine to recognize the user's "expectations and anxieties" and proposes a technology training program or mental support sessions.

[0410] Examples of prompts include, "Analyze the sentiment of the following text: 'I'm excited to learn technology, but I'm also a little anxious.'" and "The user is feeling anxious. Generate a career plan that addresses this." This enables the creation of flexible and effective career plans that take into account the individual emotional state of each user.

[0411] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0412] Step 1:

[0413] The user inputs information about their work history, feelings, and career vision through their device. The input information is temporarily stored on the device, and the emotion engine is activated. The emotion engine analyzes the input text using natural language processing technology and extracts the user's emotions as numerical data. The input is text data, and the output is an emotion score.

[0414] Step 2:

[0415] The terminal sends user data, along with analyzed sentiment information, to the server. Based on the received data, the server uses an analysis algorithm to evaluate the user's occupational needs. Here, the input is user data and sentiment score, and the output is the user's career needs evaluation data.

[0416] Step 3:

[0417] The server generates an optimal career plan using a generative AI model based on sentiment scores and career needs assessments. In this process, the AI ​​consults a large database to select resources and services suitable for the user. The input is career needs assessment data, and the output is career plan data.

[0418] Step 4:

[0419] The generated career plan is sent to the terminal and presented to the user. The user can review the presented career plan and customize it through the user interface. The input is the career plan data, and the output is the customized plan data from the user.

[0420] Step 5:

[0421] After the user begins taking action based on their career plan, the device periodically collects progress data and records any associated changes in their mood. This data is then sent back to the server and used to generate feedback. The input is progress and mood data, and the output is feedback data.

[0422] Step 6:

[0423] The server takes the new feedback into account and evaluates whether the user's career plan needs to be updated. If necessary, it modifies the career plan and sends it back to the terminal. The final output is the updated career plan.

[0424] 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.

[0425] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">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.

[0426] 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.

[0427] [Third Embodiment]

[0428] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0429] 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.

[0430] 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).

[0431] 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.

[0432] 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.

[0433] 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).

[0434] 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.

[0435] 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.

[0436] 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.

[0437] 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.

[0438] 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.

[0439] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0440] This invention relates to the realization of a support system that enables users living in the era of 100-year lifespans to achieve a fulfilling second career. The embodiments for carrying out this invention are described below.

[0441] The system begins with the user entering their work history, skills, and desired career details. The user does this through an interface on a terminal. The terminal receives the entered data and sends it to the server.

[0442] The server stores the received information in a database and analyzes the data using artificial intelligence. The AI ​​utilizes natural language processing and machine learning techniques to analyze user needs. This generates a second career plan tailored to the user's situation. This plan is optimized considering the user's experience, desires, and current social circumstances.

[0443] The generated plan is sent from the server to the terminal and presented to the user in a visual or interactive format. Users can then customize the presented plan to suit their own needs. As users customize, the system provides advice as needed, which may include access to additional information and learning resources related to their career plan.

[0444] Subsequently, as the user executes the plan, they periodically report their progress to the system via their terminal. The server generates feedback based on the reported progress information and provides guidance for the next steps. This allows the user to concretize the actions needed to achieve their goals and continuously improve.

[0445] For example, if a retired user expresses a desire to start an NPO, the system will consider the user's work history and volunteer experience and present a plan outlining the necessary skills, knowledge, and relevant organizations for NPO activities. The user can then customize the proposed plan and receive links and advice for learning the necessary skills through online courses.

[0446] In this way, the present invention provides concrete support for users to find and realize career plans that meet their individual needs.

[0447] The following describes the processing flow.

[0448] Step 1:

[0449] The user logs into the career support system and accesses a form to enter their profile. The user enters their work history, skills, and desired career information, and then clicks the submit button.

[0450] Step 2:

[0451] The terminal receives the information entered by the user, formats it, and then sends the data to the server. It then verifies that the data has been successfully transmitted.

[0452] Step 3:

[0453] The server receives data from the terminal, saves it to a database, and launches an artificial intelligence analysis tool. Based on the saved data, the AI ​​analyzes the user's needs and preferences.

[0454] Step 4:

[0455] The server generates a career plan tailored to the user based on AI analysis results. It also provides related options and information for the generated plan.

[0456] Step 5:

[0457] The server generates a carrier plan and sends it to the terminal for display to the user. The plan is made visually verifiable on the user interface.

[0458] Step 6:

[0459] The user reviews the presented plan and considers the details. The user selects the items they want to customize and enters any necessary changes or additional information.

[0460] Step 7:

[0461] The device sends user customization information to the server. The server readjusts the plan based on the received information and generates an updated plan.

[0462] Step 8:

[0463] Based on the new plan determined by the server, AI is used to provide relevant advice and resource information to the user. The necessary information is then reflected in the user interface.

[0464] Step 9:

[0465] The user begins implementing their career plan and periodically records their progress via their device. The progress data is then updated and sent.

[0466] Step 10:

[0467] The server receives progress information, and the AI ​​analyzes this data to generate feedback and suggestions for the next steps. The generated feedback is then sent to the user.

[0468] (Example 1)

[0469] Next, we will describe 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."

[0470] In modern society, with increasing life expectancy, workers have a growing need to pursue diverse professional experiences and second career paths. However, there is insufficient concrete support for effectively utilizing individual experiences and skills and setting new career goals. Traditional vocational support systems lack the provision of flexible plans tailored to individual needs and continuous feedback based on progress, and this deficiency reduces the effectiveness of career changes.

[0471] 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.

[0472] In this invention, the server includes information receiving means, storage means, analysis means, planning means including a generative AI model, customization support means, support means, and progress information tracking and feedback means. This allows users to generate an optimized career plan based on their career history and skills, customize that plan, and receive feedback based on their progress. This enables career support tailored to individual needs and promotes effective career changes.

[0473] An "information receiving means" is a mechanism for receiving information about the user's background, skills, and desired occupation via a terminal to a server.

[0474] A "storage device" is a device that stores received user information in a storage device such as a database, making it available for later analysis and plan generation.

[0475] "Analysis methods" refer to techniques that use natural language processing and machine learning technologies to analyze stored user information and reveal user characteristics and needs.

[0476] A "generative AI model" is a generative algorithm or system that automatically creates a career plan optimized for the user based on analyzed information.

[0477] A "plan creation mechanism" is a system that uses generative AI models or similar tools to create and propose career plans to users.

[0478] "Customization support means" refers to a function that supports users in adjusting and modifying the generated career plan to suit their own needs.

[0479] "Support tools" refer to functions that provide access to necessary additional information and learning resources when customizing the plan.

[0480] "Progress tracking and feedback mechanisms" refer to a system that monitors the progress of users in executing their work plans and uses that information to provide suggestions for improvement and guidance for the next steps.

[0481] This invention begins with the user inputting their career history, skills, and desired occupation information. The user inputs this information via an interface on a terminal, and the terminal transmits this information to a server. The server stores the received information in a storage device and analyzes the data using analytical means. Here, natural language processing (NLP) and machine learning techniques are utilized to perform analysis in order to understand the user's characteristics and needs. The hardware used includes general-purpose computers and server systems, and the software includes NLP and machine learning libraries.

[0482] The server uses an AI model based on the analyzed information to create an optimal career plan for the user. In this planning process, an automatically generated plan is proposed to the user. The user can visually review this plan through the terminal interface and adjust the proposed career plan to their own needs using customization support tools. During customization, the support tools provide access to necessary additional information and learning resources.

[0483] During plan execution, users report progress information from their terminals to the server. The server uses progress tracking and feedback mechanisms to monitor the user's progress and provide feedback. This allows users to receive specific guidance for the next steps.

[0484] As a concrete example, consider a retired user who wishes to start a non-profit activity. In this case, the user's background and past volunteer work are taken into consideration, and a plan can be presented that includes the skills necessary for non-profit activities and information on relevant organizations. Furthermore, the user can customize the presented plan and receive links and advice to learn the necessary skills online. An example of a prompt would be, "Generate a plan for non-profit activities based on the user's work history, skills, and desired career details."

[0485] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0486] Step 1:

[0487] Users input their work history, skills, and desired occupation information through an interface on their device. This generates text data about their past jobs and specific skills. This input data is then sent to the server in the next step.

[0488] Step 2:

[0489] The terminal sends the information received from the user to the server as data packets. The server receives these packets and stores them in its storage device. At this point, all of the user's input information is stored in a structured format and is ready for later analysis.

[0490] Step 3:

[0491] The server processes the stored data using analytical tools. Specifically, it extracts keywords from text data using natural language processing (NLP) techniques, and machine learning algorithms analyze user characteristics and needs based on this information. The input data is converted into feature vectors that reflect the user's characteristics, and the results are output.

[0492] Step 4:

[0493] The server generates an optimal career plan for the user using an AI model based on the analysis results. This process is triggered by prompt messages, which cause the AI ​​model to output multiple career plans. The output plans are recommended plans selected based on the user's characteristics.

[0494] Step 5:

[0495] The server sends the generated job plan to the terminal. The user visually reviews the plan through the terminal's interface and adjusts it as needed using customization support tools. This process requires new data based on the user's customization choices as input, and the result is output as an updated plan.

[0496] Step 6:

[0497] Users execute a plan and periodically report their progress from their terminal to the server. The server tracks the progress information and generates and outputs feedback based on the progress data. Users use this feedback to obtain specific guidance for moving on to the next step.

[0498] (Application Example 1)

[0499] Next, we will explain Application Example 1. In the following explanation, 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."

[0500] In an era of 100-year lifespans, individual citizens need personalized information and support to build new careers by appropriately utilizing their diverse backgrounds and skills, in order to achieve fulfilling second careers. However, in reality, there is a lack of systems that provide such personalized support, and in particular, support that effectively utilizes the resources of the entire city is not being provided. As a result, there is a challenge in that it is difficult for each citizen to find a suitable career plan and work towards achieving it.

[0501] 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.

[0502] In this invention, the server includes means for receiving and collecting user input, analysis means including artificial intelligence for analyzing the collected user information, and means for optimizing career plans by utilizing resources throughout the city. As a result, users can obtain an optimal career plan based on their own experience and skills, and by utilizing diverse resources within the city, the feasibility of the plan is increased, enabling a smooth transition to a second career.

[0503] "Means for receiving and collecting user input" refers to an interface for system users to input information such as their work history, skills, and career aspirations, as well as the technical means for appropriately collecting this information.

[0504] The "analysis method" is a processing system that uses artificial intelligence to analyze data based on collected user information and constructs the optimal career plan for each individual user.

[0505] The "plan proposal method" is a function that generates and presents the optimal second career plan for the user based on the analyzed information.

[0506] "Means of enabling customization" refers to technologies that allow users to adjust and modify a proposed career plan according to their own needs and conditions.

[0507] "Support tools" refer to features that provide additional advice and information when users consult about their plans.

[0508] "A means of optimizing career planning by utilizing resources throughout the city" refers to a system that enhances the feasibility of users' career plans by utilizing various resources available within the city, such as education, vocational training, and community programs.

[0509] "Means for tracking progress and providing feedback" refers to technologies that help users achieve their goals by tracking the progress of plans they have worked on and providing appropriate feedback.

[0510] To implement this invention, the user needs an electronic device, such as a smartphone or terminal. The user uses an application with an interface for inputting information about their background, skills, and career. This application is developed using Flutter and is cross-platform compatible.

[0511] The terminal receives information entered by the user and sends it to the server. The server manages this information using the Django framework and analyzes the collected data using the scikit-learn library. Through this analysis, an optimal second career plan is generated. By optimizing the plan by considering the resources of the entire city relevant to the user, a more practical proposal becomes possible.

[0512] The generated career plan is sent to the device and presented to the user visually. The user can then customize the plan to suit their preferences and circumstances. Furthermore, the system's generating AI model operates in the background to provide additional advice and information, supporting the user in achieving their desired career path.

[0513] The server tracks the progress of plans implemented by users and provides necessary feedback. It also helps lower barriers to implementation by informing users about various resources within the city. Based on this feedback, users can continue their efforts towards achieving their goals.

[0514] For example, if a user expresses a desire to participate in local cultural activities, the system will incorporate local cultural organizations, events, and related learning resources into their career plan and suggest concrete steps toward participation. The following is an example of a prompt from this system.

[0515] Example prompt: "Based on your background and skills, I propose a plan for participation in the town's cultural activities. Specifically, you may consider engaging in the following activities..."

[0516] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0517] Step 1:

[0518] The user launches an application on their smartphone and enters information about their work history, skills, and career goals. The entered data is collected and temporarily stored through the interface on the device, and then prepared to be sent to the server.

[0519] Step 2:

[0520] The terminal sends the input data received from the user to the server. The data is sent in JSON format, and the server receives it using the Django framework and securely stores it in the database. This ensures the secure storage of user information.

[0521] Step 3:

[0522] The server analyzes the received user information using the scikit-learn library. This analysis involves pattern recognition and clustering based on the input data, laying the foundation for an optimal career plan for the user. The analysis results are then ready to be input into the generative AI model.

[0523] Step 4:

[0524] The server uses an AI model to generate an optimal career plan, taking into account user preferences and the resources of the entire city, based on analysis results obtained through machine learning. The output at this stage is an individualized career plan.

[0525] Step 5:

[0526] The generated carrier plan is sent from the server to the device and visually presented to the user via the application. The user is then shown options to customize the plan, allowing them to adjust it to suit their own needs.

[0527] Step 6:

[0528] When a user takes action towards completing a career, the device periodically reports progress information to the server. Based on this information, the server generates feedback and provides advice for the next steps.

[0529] Step 7:

[0530] As support throughout the process, the server continuously provides suggestions and advice to the user using example prompts and related information. These prompts are dynamically generated using a generative AI model and provided to the user in a specific form, such as, "Based on your background and skills, we propose a plan for participating in local cultural activities."

[0531] 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.

[0532] This invention relates to a system that provides support tailored to the individual needs of users as they pursue a second career. In particular, it achieves more accurate support by using an emotion engine that recognizes and considers the user's emotions.

[0533] The system begins with the user entering information about their career. The user inputs information about their work history, current feelings, and desired career vision via a device. At this stage, the device activates an emotion engine that analyzes the user's emotions behind the entered information.

[0534] The analyzed emotional information is sent to a server and comprehensively analyzed by artificial intelligence in conjunction with the user's career aspirations. Based on this analysis, the server generates a career plan that takes the user's emotions into consideration. For example, if a user feels anxious about a particular work environment, the system will suggest an approach that reflects those emotions and recommend appropriate resources and support.

[0535] The generated plan is presented to the user via their device, and the user can customize it to reflect their emotions. Furthermore, when the user requests advice, the emotion engine reactivates to provide advice that reflects the user's current feelings. Through this process, the realization of a second career that meets the user's emotional needs is supported.

[0536] Furthermore, after users begin implementing their career plan, they can periodically report their progress via their device. This progress information is sent to the server, where the emotion engine re-evaluates the user's emotional state. The server uses this information to optimize feedback and help users effectively progress towards their desired career goals.

[0537] For example, if a user is aiming to become an independent freelance consultant, and the emotion engine detects "anxiety and anticipation" at the time of input, the system will also provide information on risk management courses and mental support that correspond to those emotions. In this way, an environment is created where users can take new steps with a more personalized plan, while also considering emotional aspects.

[0538] The following describes the processing flow.

[0539] Step 1:

[0540] The user accesses their device and logs into the career support system. The user fills out a form with details about their work history, skills, and desired second career.

[0541] Step 2:

[0542] The terminal receives user input and activates an emotion engine to recognize the emotions contained in it. The emotion engine analyzes the input data and identifies the user's emotional state.

[0543] Step 3:

[0544] The device sends input information and associated emotional information to the server. Upon receiving the data, the server stores it in a database and begins a comprehensive data analysis using an AI analysis tool.

[0545] Step 4:

[0546] The server analyzes the user's information and emotional state to generate a career plan tailored to the user. The generated plan incorporates elements that take the user's emotions into consideration.

[0547] Step 5:

[0548] The server sends a generated carrier plan to the terminal and presents it visually to the user. The user can review the plan and customize it to suit their needs.

[0549] Step 6:

[0550] Users can review the plan and make customizations related to specific emotions. If the user enters additional information, the device sends it back to the server.

[0551] Step 7:

[0552] The server receives updated information, re-evaluates the plan, and fine-tunes the approach. If necessary, the emotion engine generates emotional feedback and provides advice to the user.

[0553] Step 8:

[0554] The user begins executing the plan, recording and reporting progress via their device. The device then sends this progress data to the server.

[0555] Step 9:

[0556] The server analyzes progress information and uses an emotion engine to evaluate the user's emotional state. Based on the analysis results, it generates feedback and sends a next action plan to the user.

[0557] (Example 2)

[0558] Next, we will describe 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."

[0559] In today's world, it is difficult for individual users to effectively develop career plans that take their own emotions into account. This problem stems from a lack of detailed support to help users achieve their desired careers. Furthermore, the lack of emotion-based planning makes it difficult to alleviate user anxiety and stress during the career selection process. To solve these challenges, a system is needed that can recognize users' individual needs at an emotional level and propose optimized career plans.

[0560] 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.

[0561] In this invention, the server includes emotion analysis means for analyzing the user's emotional information and extracting the underlying emotions; analysis means for comprehensively analyzing the transmitted emotional information and career aspirations to generate an optimal career plan for the user; and feedback generation means for optimizing feedback based on the emotional information and providing it to the user. This enables users to develop career plans that take their individual emotions into account, reducing anxiety about career choices and enabling them to effectively achieve their career goals.

[0562] A "user" refers to an individual who intends to use this system to develop a career plan.

[0563] A "terminal" refers to an electronic device used by a user to input information or view generated carrier plans.

[0564] "Work history" refers to information about the occupations and work experience a user has held up to date.

[0565] "Feelings" refers to the user's current emotions and psychological state.

[0566] "Career vision" refers to the professional goals and visions that a user hopes to achieve in the future.

[0567] "Emotional analysis methods" refer to technologies and methods for extracting the underlying emotions based on information entered by the user.

[0568] "Information transfer means" refers to the technology and processes used to transmit analyzed emotional information to a server.

[0569] "Analysis means" refers to the technology within the system that comprehensively analyzes the user's emotional information and career aspirations to generate the optimal career plan.

[0570] "Plan presentation method" refers to the interface or technology used to display the generated career plan to the user and allow for customization.

[0571] "Re-evaluation methods" refer to technologies for re-evaluating a user's emotional state based on their progress information.

[0572] "Feedback generation means" refers to technologies and processes for generating feedback to be provided to users based on emotional information.

[0573] To implement this invention, the following means are used. First, the user inputs their work history, feelings, and desired career vision using a terminal. The terminal provides a user interface that makes it easy for the user to operate while collecting this information.

[0574] Subsequently, the device uses emotion analysis tools to analyze the user's input information and extract the underlying emotions. Natural Language Processing (NLP) technology is used for this emotion analysis. For example, emotional states such as "anxiety" and "expectation" are tagged.

[0575] The analyzed emotional information is encrypted by the information transfer method and sent to the server via a secure protocol. The server uses an artificial intelligence model as an analysis tool to comprehensively analyze the user's emotional information and career aspirations and generate an optimal career plan. This analysis process involves machine learning algorithms and inference based on similar past cases.

[0576] The generated career plan is presented to the user on their device using a plan presentation tool. Users can customize this plan, adjusting it to their liking using drag-and-drop or direct editing functions.

[0577] Furthermore, when a user begins taking action based on a generated plan, a re-evaluation mechanism is periodically activated to re-evaluate their emotional state based on progress information. Based on this information, the server uses a feedback generation mechanism to provide optimized feedback to the user.

[0578] As a concrete example, consider a case where a user is a freelance consultant who wants to become independent. If this user consults about feelings such as "anxiety and excitement," the system will suggest risk management courses and mental support information specifically tailored to these emotions.

[0579] An example of a prompt generated using an AI model might be: "I'm feeling anxious about my career as a freelance consultant. How can I alleviate my anxiety and move on to the next step?" This prompt allows the AI ​​to provide the user with appropriate advice and resources.

[0580] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0581] Step 1:

[0582] The user uses the terminal to input their work history, current feelings, and desired career vision. The entered data is imported into the terminal via the user interface. The terminal displays a guide to help the user input all the necessary information without omission.

[0583] Step 2:

[0584] The terminal activates an emotion analysis system based on the input data. This system uses Natural Language Processing (NLP) technology to analyze the text data and extract emotion tags. For example, emotions such as "anxiety" and "anticipation" may be detected. The analysis results are output as numerical values ​​or tags representing the user's emotional state.

[0585] Step 3:

[0586] The terminal transmits the extracted sentiment information and user input data to the server using an information transfer method. During this process, the data is encrypted using a secure protocol. The server receives this encrypted data and converts the data structure into a format suitable for analysis.

[0587] Step 4:

[0588] The server performs a comprehensive analysis using analytical tools based on the received data. Specifically, it uses a generative AI model and machine learning algorithms to analyze the user's emotions and career aspirations. The server searches a database of similar cases and performs pattern recognition to generate the optimal career plan. Through this process, a career plan tailored to the user is output.

[0589] Step 5:

[0590] The generated career plan is sent from the server to the device. The device uses a plan presentation tool to visually display this plan to the user. The user can review the plan's contents and customize it to their own feelings and goals through drag-and-drop or direct editing.

[0591] Step 6:

[0592] After the user begins executing their career plan, the device collects progress information and sends it to the server. The server periodically activates a re-evaluation mechanism to reassess the emotional state based on the progress information. Based on this analysis, the server generates any necessary feedback.

[0593] Step 7:

[0594] The re-evaluation results and optimized feedback are sent to the device using a feedback generation mechanism. The device presents the feedback to the user, allowing them to further adjust their actions on the spot. This entire process enables the user to engage in continuous career planning that takes their own emotions into account.

[0595] (Application Example 2)

[0596] Next, we will explain application example 2. In the following explanation, 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."

[0597] In modern society, when citizens venture into new professions or fields, they require specific support tailored to their individual emotions and needs. However, current systems lack sufficient support that adequately considers users' emotions, making it difficult to provide comprehensive and flexible career plans. Therefore, the challenge lies in accurately understanding users' emotions and providing the most appropriate resources and approaches accordingly.

[0598] 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.

[0599] In this invention, the server includes a device for receiving and collecting user input, an automated analysis device for analyzing the collected user information, and a device for considering the analyzed emotional information and presenting the user with resources that correspond to their emotions. This makes it possible to provide a flexible and personalized career plan that takes the user's emotions into consideration.

[0600] A "device that receives and collects user input" is equipment that acquires occupation-related information and emotional data from users and stores it within the system.

[0601] An "automated analysis device" is a piece of equipment that uses artificial intelligence to analyze collected user information and evaluate emotions and occupational needs.

[0602] A "proposal device" is equipment that generates and presents an optimal career plan to the user based on the analysis results.

[0603] A "device that presents a generated occupational plan to the user and allows for modifications" is equipment that displays the generated occupational plan to the user and provides the function to modify or customize it.

[0604] A "support device" is equipment designed to provide appropriate advice and resources in response to additional inquiries from users.

[0605] A "feedback generating device" is equipment that collects user career progress information and generates appropriate opinions based on changes in their emotional state.

[0606] A "device that presents resources according to emotions" is equipment that provides useful resources and support appropriate to the user's situation, based on their analyzed emotions.

[0607] This system receives career-related information from users and provides personalized career plans. Information entered through the user's terminal primarily includes work history, feelings, and career vision. This information is collected by a terminal with emotion recognition capabilities, which activates an emotion engine to analyze the user's emotions. The software used at this stage includes the "transformers" (Hugging Face) library for natural language processing.

[0608] The server uses analyzed emotional and career information to generate a comprehensive career plan, leveraging artificial intelligence. This process suggests the most suitable resources and support tools to the user based on the emotional analysis results. For example, if the analysis reveals the user is experiencing anxiety in a new field, the server will recommend risk management and mental support courses.

[0609] Users can review the career plan presented through their device and customize it based on their emotions. Regular progress reports provide feedback and advice tailored to their emotional state. Throughout this process, the server adjusts the plan based on the feedback, continuously supporting the user in achieving their goals.

[0610] For example, if a user wants to build a career in a new technology field, they might input thoughts like, "I'm excited about learning the technology, but I'm also a little anxious." In this case, the server uses an emotion engine to recognize the user's "expectations and anxieties" and proposes a technology training program or mental support sessions.

[0611] Examples of prompts include, "Analyze the sentiment of the following text: 'I'm excited to learn technology, but I'm also a little anxious.'" and "The user is feeling anxious. Generate a career plan that addresses this." This enables the creation of flexible and effective career plans that take into account the individual emotional state of each user.

[0612] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0613] Step 1:

[0614] The user inputs information about their work history, feelings, and career vision through their device. The input information is temporarily stored on the device, and the emotion engine is activated. The emotion engine analyzes the input text using natural language processing technology and extracts the user's emotions as numerical data. The input is text data, and the output is an emotion score.

[0615] Step 2:

[0616] The terminal sends user data, along with analyzed sentiment information, to the server. Based on the received data, the server uses an analysis algorithm to evaluate the user's occupational needs. Here, the input is user data and sentiment score, and the output is the user's career needs evaluation data.

[0617] Step 3:

[0618] The server generates an optimal career plan using a generative AI model based on sentiment scores and career needs assessments. In this process, the AI ​​consults a large database to select resources and services suitable for the user. The input is career needs assessment data, and the output is career plan data.

[0619] Step 4:

[0620] The generated career plan is sent to the terminal and presented to the user. The user can review the presented career plan and customize it through the user interface. The input is the career plan data, and the output is the customized plan data from the user.

[0621] Step 5:

[0622] After the user begins taking action based on their career plan, the device periodically collects progress data and records any associated changes in their mood. This data is then sent back to the server and used to generate feedback. The input is progress and mood data, and the output is feedback data.

[0623] Step 6:

[0624] The server takes the new feedback into account and evaluates whether the user's career plan needs to be updated. If necessary, it modifies the career plan and sends it back to the terminal. The final output is the updated career plan.

[0625] 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.

[0626] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">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.

[0627] 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.

[0628] [Fourth Embodiment]

[0629] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0630] 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.

[0631] 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).

[0632] 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.

[0633] 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.

[0634] 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).

[0635] 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.

[0636] 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.

[0637] 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.

[0638] 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.

[0639] 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.

[0640] 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.

[0641] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0642] This invention relates to the realization of a support system that enables users living in the era of 100-year lifespans to achieve a fulfilling second career. The embodiments for carrying out this invention are described below.

[0643] The system begins with the user entering their work history, skills, and desired career details. The user does this through an interface on a terminal. The terminal receives the entered data and sends it to the server.

[0644] The server stores the received information in a database and analyzes the data using artificial intelligence. The AI ​​utilizes natural language processing and machine learning techniques to analyze user needs. This generates a second career plan tailored to the user's situation. This plan is optimized considering the user's experience, desires, and current social circumstances.

[0645] The generated plan is sent from the server to the terminal and presented to the user in a visual or interactive format. Users can then customize the presented plan to suit their own needs. As users customize, the system provides advice as needed, which may include access to additional information and learning resources related to their career plan.

[0646] Subsequently, as the user executes the plan, they periodically report their progress to the system via their terminal. The server generates feedback based on the reported progress information and provides guidance for the next steps. This allows the user to concretize the actions needed to achieve their goals and continuously improve.

[0647] For example, if a retired user expresses a desire to start an NPO, the system will consider the user's work history and volunteer experience and present a plan outlining the necessary skills, knowledge, and relevant organizations for NPO activities. The user can then customize the proposed plan and receive links and advice for learning the necessary skills through online courses.

[0648] In this way, the present invention provides concrete support for users to find and realize career plans that meet their individual needs.

[0649] The following describes the processing flow.

[0650] Step 1:

[0651] The user logs into the career support system and accesses a form to enter their profile. The user enters their work history, skills, and desired career information, and then clicks the submit button.

[0652] Step 2:

[0653] The terminal receives the information entered by the user, formats it, and then sends the data to the server. It then verifies that the data has been successfully transmitted.

[0654] Step 3:

[0655] The server receives data from the terminal, saves it to a database, and launches an artificial intelligence analysis tool. Based on the saved data, the AI ​​analyzes the user's needs and preferences.

[0656] Step 4:

[0657] The server generates a career plan tailored to the user based on AI analysis results. It also provides related options and information for the generated plan.

[0658] Step 5:

[0659] The server generates a carrier plan and sends it to the terminal for display to the user. The plan is made visually verifiable on the user interface.

[0660] Step 6:

[0661] The user reviews the presented plan and considers the details. The user selects the items they want to customize and enters any necessary changes or additional information.

[0662] Step 7:

[0663] The device sends user customization information to the server. The server readjusts the plan based on the received information and generates an updated plan.

[0664] Step 8:

[0665] Based on the new plan determined by the server, AI is used to provide relevant advice and resource information to the user. The necessary information is then reflected in the user interface.

[0666] Step 9:

[0667] The user begins implementing their career plan and periodically records their progress via their device. The progress data is then updated and sent.

[0668] Step 10:

[0669] The server receives progress information, and the AI ​​analyzes this data to generate feedback and suggestions for the next steps. The generated feedback is then sent to the user.

[0670] (Example 1)

[0671] Next, we will describe 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".

[0672] In modern society, with increasing life expectancy, workers have a growing need to pursue diverse professional experiences and second career paths. However, there is insufficient concrete support for effectively utilizing individual experiences and skills and setting new career goals. Traditional vocational support systems lack the provision of flexible plans tailored to individual needs and continuous feedback based on progress, and this deficiency reduces the effectiveness of career changes.

[0673] 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.

[0674] In this invention, the server includes information receiving means, storage means, analysis means, planning means including a generative AI model, customization support means, support means, and progress information tracking and feedback means. This allows users to generate an optimized career plan based on their career history and skills, customize that plan, and receive feedback based on their progress. This enables career support tailored to individual needs and promotes effective career changes.

[0675] An "information receiving means" is a mechanism for receiving information about the user's background, skills, and desired occupation via a terminal to a server.

[0676] A "storage device" is a device that stores received user information in a storage device such as a database, making it available for later analysis and plan generation.

[0677] "Analysis methods" refer to techniques that use natural language processing and machine learning technologies to analyze stored user information and reveal user characteristics and needs.

[0678] A "generative AI model" is a generative algorithm or system that automatically creates a career plan optimized for the user based on analyzed information.

[0679] A "plan creation mechanism" is a system that uses generative AI models or similar tools to create and propose career plans to users.

[0680] "Customization support means" refers to a function that supports users in adjusting and modifying the generated career plan to suit their own needs.

[0681] "Support tools" refer to functions that provide access to necessary additional information and learning resources when customizing the plan.

[0682] "Progress tracking and feedback mechanisms" refer to a system that monitors the progress of users in executing their work plans and uses that information to provide suggestions for improvement and guidance for the next steps.

[0683] This invention begins with the user inputting their career history, skills, and desired occupation information. The user inputs this information via an interface on a terminal, and the terminal transmits this information to a server. The server stores the received information in a storage device and analyzes the data using analytical means. Here, natural language processing (NLP) and machine learning techniques are utilized to perform analysis in order to understand the user's characteristics and needs. The hardware used includes general-purpose computers and server systems, and the software includes NLP and machine learning libraries.

[0684] The server uses an AI model based on the analyzed information to create an optimal career plan for the user. In this planning process, an automatically generated plan is proposed to the user. The user can visually review this plan through the terminal interface and adjust the proposed career plan to their own needs using customization support tools. During customization, the support tools provide access to necessary additional information and learning resources.

[0685] During plan execution, users report progress information from their terminals to the server. The server uses progress tracking and feedback mechanisms to monitor the user's progress and provide feedback. This allows users to receive specific guidance for the next steps.

[0686] As a concrete example, consider a retired user who wishes to start a non-profit activity. In this case, the user's background and past volunteer work are taken into consideration, and a plan can be presented that includes the skills necessary for non-profit activities and information on relevant organizations. Furthermore, the user can customize the presented plan and receive links and advice to learn the necessary skills online. An example of a prompt would be, "Generate a plan for non-profit activities based on the user's work history, skills, and desired career details."

[0687] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0688] Step 1:

[0689] Users input their work history, skills, and desired occupation information through an interface on their device. This generates text data about their past jobs and specific skills. This input data is then sent to the server in the next step.

[0690] Step 2:

[0691] The terminal sends the information received from the user to the server as data packets. The server receives these packets and stores them in its storage device. At this point, all of the user's input information is stored in a structured format and is ready for later analysis.

[0692] Step 3:

[0693] The server processes the stored data using analytical tools. Specifically, it extracts keywords from text data using natural language processing (NLP) techniques, and machine learning algorithms analyze user characteristics and needs based on this information. The input data is converted into feature vectors that reflect the user's characteristics, and the results are output.

[0694] Step 4:

[0695] The server generates an optimal career plan for the user using an AI model based on the analysis results. This process is triggered by prompt messages, which cause the AI ​​model to output multiple career plans. The output plans are recommended plans selected based on the user's characteristics.

[0696] Step 5:

[0697] The server sends the generated job plan to the terminal. The user visually reviews the plan through the terminal's interface and adjusts it as needed using customization support tools. This process requires new data based on the user's customization choices as input, and the result is output as an updated plan.

[0698] Step 6:

[0699] Users execute a plan and periodically report their progress from their terminal to the server. The server tracks the progress information and generates and outputs feedback based on the progress data. Users use this feedback to obtain specific guidance for moving on to the next step.

[0700] (Application Example 1)

[0701] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0702] In an era of 100-year lifespans, individual citizens need personalized information and support to build new careers by appropriately utilizing their diverse backgrounds and skills, in order to achieve fulfilling second careers. However, in reality, there is a lack of systems that provide such personalized support, and in particular, support that effectively utilizes the resources of the entire city is not being provided. As a result, there is a challenge in that it is difficult for each citizen to find a suitable career plan and work towards achieving it.

[0703] 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.

[0704] In this invention, the server includes means for receiving and collecting user input, analysis means including artificial intelligence for analyzing the collected user information, and means for optimizing career plans by utilizing resources throughout the city. As a result, users can obtain an optimal career plan based on their own experience and skills, and by utilizing diverse resources within the city, the feasibility of the plan is increased, enabling a smooth transition to a second career.

[0705] "Means for receiving and collecting user input" refers to an interface for system users to input information such as their work history, skills, and career aspirations, as well as the technical means for appropriately collecting this information.

[0706] The "analysis method" is a processing system that uses artificial intelligence to analyze data based on collected user information and constructs the optimal career plan for each individual user.

[0707] The "plan proposal method" is a function that generates and presents the optimal second career plan for the user based on the analyzed information.

[0708] "Means of enabling customization" refers to technologies that allow users to adjust and modify a proposed career plan according to their own needs and conditions.

[0709] "Support tools" refer to features that provide additional advice and information when users consult about their plans.

[0710] "A means of optimizing career planning by utilizing resources throughout the city" refers to a system that enhances the feasibility of users' career plans by utilizing various resources available within the city, such as education, vocational training, and community programs.

[0711] "Means for tracking progress and providing feedback" refers to technologies that help users achieve their goals by tracking the progress of plans they have worked on and providing appropriate feedback.

[0712] To implement this invention, the user needs an electronic device, such as a smartphone or terminal. The user uses an application with an interface for inputting information about their background, skills, and career. This application is developed using Flutter and is cross-platform compatible.

[0713] The terminal receives information entered by the user and sends it to the server. The server manages this information using the Django framework and analyzes the collected data using the scikit-learn library. Through this analysis, an optimal second career plan is generated. By optimizing the plan by considering the resources of the entire city relevant to the user, a more practical proposal becomes possible.

[0714] The generated career plan is sent to the device and presented to the user visually. The user can then customize the plan to suit their preferences and circumstances. Furthermore, the system's generating AI model operates in the background to provide additional advice and information, supporting the user in achieving their desired career path.

[0715] The server tracks the progress of plans implemented by users and provides necessary feedback. It also helps lower barriers to implementation by informing users about various resources within the city. Based on this feedback, users can continue their efforts towards achieving their goals.

[0716] For example, if a user expresses a desire to participate in local cultural activities, the system will incorporate local cultural organizations, events, and related learning resources into their career plan and suggest concrete steps toward participation. The following is an example of a prompt from this system.

[0717] Example prompt: "Based on your background and skills, I propose a plan for participation in the town's cultural activities. Specifically, you may consider engaging in the following activities..."

[0718] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0719] Step 1:

[0720] The user launches an application on their smartphone and enters information about their work history, skills, and career goals. The entered data is collected and temporarily stored through the interface on the device, and then prepared to be sent to the server.

[0721] Step 2:

[0722] The terminal sends the input data received from the user to the server. The data is sent in JSON format, and the server receives it using the Django framework and securely stores it in the database. This ensures the secure storage of user information.

[0723] Step 3:

[0724] The server analyzes the received user information using the scikit-learn library. This analysis involves pattern recognition and clustering based on the input data, laying the foundation for an optimal career plan for the user. The analysis results are then ready to be input into the generative AI model.

[0725] Step 4:

[0726] The server uses an AI model to generate an optimal career plan, taking into account user preferences and the resources of the entire city, based on analysis results obtained through machine learning. The output at this stage is an individualized career plan.

[0727] Step 5:

[0728] The generated carrier plan is sent from the server to the device and visually presented to the user via the application. The user is then shown options to customize the plan, allowing them to adjust it to suit their own needs.

[0729] Step 6:

[0730] When a user takes action towards completing a career, the device periodically reports progress information to the server. Based on this information, the server generates feedback and provides advice for the next steps.

[0731] Step 7:

[0732] As support throughout the process, the server continuously provides suggestions and advice to the user using example prompts and related information. These prompts are dynamically generated using a generative AI model and provided to the user in a specific form, such as, "Based on your background and skills, we propose a plan for participating in local cultural activities."

[0733] 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.

[0734] This invention relates to a system that provides support tailored to the individual needs of users as they pursue a second career. In particular, it achieves more accurate support by using an emotion engine that recognizes and considers the user's emotions.

[0735] The system begins with the user entering information about their career. The user inputs information about their work history, current feelings, and desired career vision via a device. At this stage, the device activates an emotion engine that analyzes the user's emotions behind the entered information.

[0736] The analyzed emotional information is sent to a server and comprehensively analyzed by artificial intelligence in conjunction with the user's career aspirations. Based on this analysis, the server generates a career plan that takes the user's emotions into consideration. For example, if a user feels anxious about a particular work environment, the system will suggest an approach that reflects those emotions and recommend appropriate resources and support.

[0737] The generated plan is presented to the user via their device, and the user can customize it to reflect their emotions. Furthermore, when the user requests advice, the emotion engine reactivates to provide advice that reflects the user's current feelings. Through this process, the realization of a second career that meets the user's emotional needs is supported.

[0738] Furthermore, after users begin implementing their career plan, they can periodically report their progress via their device. This progress information is sent to the server, where the emotion engine re-evaluates the user's emotional state. The server uses this information to optimize feedback and help users effectively progress towards their desired career goals.

[0739] For example, if a user is aiming to become an independent freelance consultant, and the emotion engine detects "anxiety and anticipation" at the time of input, the system will also provide information on risk management courses and mental support that correspond to those emotions. In this way, an environment is created where users can take new steps with a more personalized plan, while also considering emotional aspects.

[0740] The following describes the processing flow.

[0741] Step 1:

[0742] The user accesses their device and logs into the career support system. The user fills out a form with details about their work history, skills, and desired second career.

[0743] Step 2:

[0744] The terminal receives user input and activates an emotion engine to recognize the emotions contained in it. The emotion engine analyzes the input data and identifies the user's emotional state.

[0745] Step 3:

[0746] The device sends input information and associated emotional information to the server. Upon receiving the data, the server stores it in a database and begins a comprehensive data analysis using an AI analysis tool.

[0747] Step 4:

[0748] The server analyzes the user's information and emotional state to generate a career plan tailored to the user. The generated plan incorporates elements that take the user's emotions into consideration.

[0749] Step 5:

[0750] The server sends a generated carrier plan to the terminal and presents it visually to the user. The user can review the plan and customize it to suit their needs.

[0751] Step 6:

[0752] Users can review the plan and make customizations related to specific emotions. If the user enters additional information, the device sends it back to the server.

[0753] Step 7:

[0754] The server receives updated information, re-evaluates the plan, and fine-tunes the approach. If necessary, the emotion engine generates emotional feedback and provides advice to the user.

[0755] Step 8:

[0756] The user begins executing the plan, recording and reporting progress via their device. The device then sends this progress data to the server.

[0757] Step 9:

[0758] The server analyzes progress information and uses an emotion engine to evaluate the user's emotional state. Based on the analysis results, it generates feedback and sends a next action plan to the user.

[0759] (Example 2)

[0760] Next, we will describe 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".

[0761] In today's world, it is difficult for individual users to effectively develop career plans that take their own emotions into account. This problem stems from a lack of detailed support to help users achieve their desired careers. Furthermore, the lack of emotion-based planning makes it difficult to alleviate user anxiety and stress during the career selection process. To solve these challenges, a system is needed that can recognize users' individual needs at an emotional level and propose optimized career plans.

[0762] 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.

[0763] In this invention, the server includes emotion analysis means for analyzing the user's emotional information and extracting the underlying emotions; analysis means for comprehensively analyzing the transmitted emotional information and career aspirations to generate an optimal career plan for the user; and feedback generation means for optimizing feedback based on the emotional information and providing it to the user. This enables users to develop career plans that take their individual emotions into account, reducing anxiety about career choices and enabling them to effectively achieve their career goals.

[0764] A "user" refers to an individual who intends to use this system to develop a career plan.

[0765] A "terminal" refers to an electronic device used by a user to input information or view generated carrier plans.

[0766] "Work history" refers to information about the occupations and work experience a user has held up to date.

[0767] "Feelings" refers to the user's current emotions and psychological state.

[0768] "Career vision" refers to the professional goals and visions that a user hopes to achieve in the future.

[0769] "Emotional analysis methods" refer to technologies and methods for extracting the underlying emotions based on information entered by the user.

[0770] "Information transfer means" refers to the technology and processes used to transmit analyzed emotional information to a server.

[0771] "Analysis means" refers to the technology within the system that comprehensively analyzes the user's emotional information and career aspirations to generate the optimal career plan.

[0772] "Plan presentation method" refers to the interface or technology used to display the generated career plan to the user and allow for customization.

[0773] "Re-evaluation methods" refer to technologies for re-evaluating a user's emotional state based on their progress information.

[0774] "Feedback generation means" refers to technologies and processes for generating feedback to be provided to users based on emotional information.

[0775] To implement this invention, the following means are used. First, the user inputs their work history, feelings, and desired career vision using a terminal. The terminal provides a user interface that makes it easy for the user to operate while collecting this information.

[0776] Subsequently, the device uses emotion analysis tools to analyze the user's input information and extract the underlying emotions. Natural Language Processing (NLP) technology is used for this emotion analysis. For example, emotional states such as "anxiety" and "expectation" are tagged.

[0777] The analyzed emotional information is encrypted by the information transfer method and sent to the server via a secure protocol. The server uses an artificial intelligence model as an analysis tool to comprehensively analyze the user's emotional information and career aspirations and generate an optimal career plan. This analysis process involves machine learning algorithms and inference based on similar past cases.

[0778] The generated career plan is presented to the user on their device using a plan presentation tool. Users can customize this plan, adjusting it to their liking using drag-and-drop or direct editing functions.

[0779] Furthermore, when a user begins taking action based on a generated plan, a re-evaluation mechanism is periodically activated to re-evaluate their emotional state based on progress information. Based on this information, the server uses a feedback generation mechanism to provide optimized feedback to the user.

[0780] As a concrete example, consider a case where a user is a freelance consultant who wants to become independent. If this user consults about feelings such as "anxiety and excitement," the system will suggest risk management courses and mental support information specifically tailored to these emotions.

[0781] An example of a prompt generated using an AI model might be: "I'm feeling anxious about my career as a freelance consultant. How can I alleviate my anxiety and move on to the next step?" This prompt allows the AI ​​to provide the user with appropriate advice and resources.

[0782] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0783] Step 1:

[0784] The user uses the terminal to input their work history, current feelings, and desired career vision. The entered data is imported into the terminal via the user interface. The terminal displays a guide to help the user input all the necessary information without omission.

[0785] Step 2:

[0786] The terminal activates an emotion analysis system based on the input data. This system uses Natural Language Processing (NLP) technology to analyze the text data and extract emotion tags. For example, emotions such as "anxiety" and "anticipation" may be detected. The analysis results are output as numerical values ​​or tags representing the user's emotional state.

[0787] Step 3:

[0788] The terminal transmits the extracted sentiment information and user input data to the server using an information transfer method. During this process, the data is encrypted using a secure protocol. The server receives this encrypted data and converts the data structure into a format suitable for analysis.

[0789] Step 4:

[0790] The server performs a comprehensive analysis using analytical tools based on the received data. Specifically, it uses a generative AI model and machine learning algorithms to analyze the user's emotions and career aspirations. The server searches a database of similar cases and performs pattern recognition to generate the optimal career plan. Through this process, a career plan tailored to the user is output.

[0791] Step 5:

[0792] The generated career plan is sent from the server to the device. The device uses a plan presentation tool to visually display this plan to the user. The user can review the plan's contents and customize it to their own feelings and goals through drag-and-drop or direct editing.

[0793] Step 6:

[0794] After the user begins executing their career plan, the device collects progress information and sends it to the server. The server periodically activates a re-evaluation mechanism to reassess the emotional state based on the progress information. Based on this analysis, the server generates any necessary feedback.

[0795] Step 7:

[0796] The re-evaluation results and optimized feedback are sent to the device using a feedback generation mechanism. The device presents the feedback to the user, allowing them to further adjust their actions on the spot. This entire process enables the user to engage in continuous career planning that takes their own emotions into account.

[0797] (Application Example 2)

[0798] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0799] In modern society, when citizens venture into new professions or fields, they require specific support tailored to their individual emotions and needs. However, current systems lack sufficient support that adequately considers users' emotions, making it difficult to provide comprehensive and flexible career plans. Therefore, the challenge lies in accurately understanding users' emotions and providing the most appropriate resources and approaches accordingly.

[0800] 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.

[0801] In this invention, the server includes a device for receiving and collecting user input, an automated analysis device for analyzing the collected user information, and a device for considering the analyzed emotional information and presenting the user with resources that correspond to their emotions. This makes it possible to provide a flexible and personalized career plan that takes the user's emotions into consideration.

[0802] A "device that receives and collects user input" is equipment that acquires occupation-related information and emotional data from users and stores it within the system.

[0803] An "automated analysis device" is a piece of equipment that uses artificial intelligence to analyze collected user information and evaluate emotions and occupational needs.

[0804] A "proposal device" is equipment that generates and presents an optimal career plan to the user based on the analysis results.

[0805] A "device that presents a generated occupational plan to the user and allows for modifications" is equipment that displays the generated occupational plan to the user and provides the function to modify or customize it.

[0806] A "support device" is equipment designed to provide appropriate advice and resources in response to additional inquiries from users.

[0807] A "feedback generating device" is equipment that collects user career progress information and generates appropriate opinions based on changes in their emotional state.

[0808] A "device that presents resources according to emotions" is equipment that provides useful resources and support appropriate to the user's situation, based on their analyzed emotions.

[0809] This system receives career-related information from users and provides personalized career plans. Information entered through the user's terminal primarily includes work history, feelings, and career vision. This information is collected by a terminal with emotion recognition capabilities, which activates an emotion engine to analyze the user's emotions. The software used at this stage includes the "transformers" (Hugging Face) library for natural language processing.

[0810] The server uses analyzed emotional and career information to generate a comprehensive career plan, leveraging artificial intelligence. This process suggests the most suitable resources and support tools to the user based on the emotional analysis results. For example, if the analysis reveals the user is experiencing anxiety in a new field, the server will recommend risk management and mental support courses.

[0811] Users can review the career plan presented through their device and customize it based on their emotions. Regular progress reports provide feedback and advice tailored to their emotional state. Throughout this process, the server adjusts the plan based on the feedback, continuously supporting the user in achieving their goals.

[0812] For example, if a user wants to build a career in a new technology field, they might input thoughts like, "I'm excited about learning the technology, but I'm also a little anxious." In this case, the server uses an emotion engine to recognize the user's "expectations and anxieties" and proposes a technology training program or mental support sessions.

[0813] Examples of prompts include, "Analyze the sentiment of the following text: 'I'm excited to learn technology, but I'm also a little anxious.'" and "The user is feeling anxious. Generate a career plan that addresses this." This enables the creation of flexible and effective career plans that take into account the individual emotional state of each user.

[0814] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0815] Step 1:

[0816] The user inputs information about their work history, feelings, and career vision through their device. The input information is temporarily stored on the device, and the emotion engine is activated. The emotion engine analyzes the input text using natural language processing technology and extracts the user's emotions as numerical data. The input is text data, and the output is an emotion score.

[0817] Step 2:

[0818] The terminal sends user data, along with analyzed sentiment information, to the server. Based on the received data, the server uses an analysis algorithm to evaluate the user's occupational needs. Here, the input is user data and sentiment score, and the output is the user's career needs evaluation data.

[0819] Step 3:

[0820] The server generates an optimal career plan using a generative AI model based on sentiment scores and career needs assessments. In this process, the AI ​​consults a large database to select resources and services suitable for the user. The input is career needs assessment data, and the output is career plan data.

[0821] Step 4:

[0822] The generated career plan is sent to the terminal and presented to the user. The user can review the presented career plan and customize it through the user interface. The input is the career plan data, and the output is the customized plan data from the user.

[0823] Step 5:

[0824] After the user begins taking action based on their career plan, the device periodically collects progress data and records any associated changes in their mood. This data is then sent back to the server and used to generate feedback. The input is progress and mood data, and the output is feedback data.

[0825] Step 6:

[0826] The server takes the new feedback into account and evaluates whether the user's career plan needs to be updated. If necessary, it modifies the career plan and sends it back to the terminal. The final output is the updated career plan.

[0827] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 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.

[0828] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">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.

[0829] In the above embodiment, an example was given in which the 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 robot 414.

[0830] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0831] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0832] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0833] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0834] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0835] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0836] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0837] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0838] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0839] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0840] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0841] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0842] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0843] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0844] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0845] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0846] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0847] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0848] The following is further disclosed regarding the embodiments described above.

[0849] (Claim 1)

[0850] Means for receiving and collecting user input,

[0851] Analysis means including artificial intelligence for analyzing collected user information,

[0852] A plan proposal method that generates the optimal career plan for the user based on the analysis results,

[0853] A means to present a generated career plan to the user and allow for customization,

[0854] A support mechanism to provide additional advice in response to inquiries from users,

[0855] A means of tracking progress information and generating feedback,

[0856] A system that includes this.

[0857] (Claim 2)

[0858] The system according to claim 1, which allows the user to select and customize a plan to adapt to specific career goals.

[0859] (Claim 3)

[0860] The system according to claim 1, comprising a user interface for visually providing user information, plan presentation, and progress management.

[0861] "Example 1"

[0862] (Claim 1)

[0863] A means of receiving information for users to input their career history, skills, and desired occupation information,

[0864] A means for storing user information collected via an information receiving means in a storage device,

[0865] An analytical method for analyzing stored user information using natural language processing and machine learning,

[0866] A planning means including a generative AI model for generating a career plan optimized for the user based on analysis results,

[0867] A means of providing customization support to present a generated career plan to the user and enable customization through a visual interface,

[0868] Support tools that provide additional information and learning resources related to the user's customized plan,

[0869] A means for tracking the progress of a user's plan execution and generating feedback based on progress information,

[0870] A system that includes this.

[0871] (Claim 2)

[0872] The system according to claim 1, which allows the user to select a plan and customize it via a visual interface to address specific occupational goals.

[0873] (Claim 3)

[0874] The system according to claim 1, comprising an interactive user interface for visually providing user information and progress management.

[0875] "Application Example 1"

[0876] (Claim 1)

[0877] Means for receiving and collecting user input,

[0878] Analysis means including artificial intelligence for analyzing collected user information,

[0879] A plan proposal means that generates an optimal career plan for the user based on the analysis results,

[0880] A means to present the generated career plan to the user and allow for customization,

[0881] In response to inquiries from users, we provide support measures to offer additional advice,

[0882] A means of optimizing career planning by utilizing resources throughout the city,

[0883] A means of tracking progress information and providing feedback through a visual interface,

[0884] A system that includes this.

[0885] (Claim 2)

[0886] The system according to claim 1, which allows the user to select and customize a plan to adapt to specific occupational goals.

[0887] (Claim 3)

[0888] The system according to claim 1, comprising a user interface that visually provides user information, plan presentation, and progress management, and displays interconnected resources within a city.

[0889] "Example 2 of combining an emotion engine"

[0890] (Claim 1)

[0891] A means for users to input their work history, current feelings, and desired career vision via their device,

[0892] A sentiment analysis tool that analyzes input information and extracts the user's emotions behind it,

[0893] An information transfer means for sending extracted emotional information to a server,

[0894] An analytical means for comprehensively analyzing transmitted emotional information and career aspirations to generate the optimal career plan for the user,

[0895] A means of presenting a generated career plan and allowing the user to customize that plan,

[0896] A re-evaluation method that tracks user progress and reassessses their emotional state,

[0897] A feedback generation method that optimizes and provides feedback to the user based on emotional information,

[0898] A system that includes this.

[0899] (Claim 2)

[0900] The system according to claim 1, which enables a user to customize a generated career plan and apply it to specific career goals.

[0901] (Claim 3)

[0902] The system according to claim 1, comprising a user interface for visually providing user information input, plan presentation, progress management, and feedback.

[0903] "Application example 2 when combining with an emotional engine"

[0904] (Claim 1)

[0905] A device that receives and collects user input,

[0906] An automated analysis device for analyzing collected user information,

[0907] A suggestion device that generates an optimal career plan for the user based on the analysis results,

[0908] A device that presents the generated job plan to the user and allows for modifications,

[0909] A support device for providing additional advice in response to user inquiries,

[0910] A device that tracks progress information and generates feedback,

[0911] A device that considers analyzed emotional information and presents the user with resources that correspond to their emotions,

[0912] A system that includes this.

[0913] (Claim 2)

[0914] The system according to claim 1, wherein the user selects and modifies a plan to adapt to specific occupational goals.

[0915] (Claim 3)

[0916] The system according to claim 1, comprising a user interface for visually providing user information, plan presentation, and progress management. [Explanation of symbols]

[0917] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means for receiving and collecting user input, Analysis means including artificial intelligence for analyzing collected user information, A plan proposal method that generates the optimal career plan for the user based on the analysis results, A means to present a generated career plan to the user and allow for customization, A support mechanism to provide additional advice in response to inquiries from users, A means of tracking progress information and generating feedback, A system that includes this.

2. The system according to claim 1, which allows the user to select and customize a plan to adapt to specific career goals.

3. The system according to claim 1, comprising a user interface for visually providing user information, plan presentation, and progress management.

Images