system

Abstract

We provide the system. [Solution] An information processing system that provides career support based on student input information, A presentation means that presents advice generated by the information processing means, A means of collecting feedback on the advice given, A database for storing the aforementioned feedback and historical data, 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 persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a 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] When students choose their career paths in the modern educational environment, they often do not receive sufficient support due to lack of information and reduction of teachers, resulting in regret about career path choices. Also, the current situation is that career counseling services are burdensome for teachers. Therefore, there is a need for a system that presents diverse career options and formulates an optimal career plan based on the student's own value system.

Means for Solving the Problems

[0005] This invention provides a system that provides career support using information processing means based on student input information. Specifically, it presents advice generated by the information processing means and collects and stores feedback to propose a career path suitable for the student. Furthermore, the advice includes industry trend information and necessary skills information, enabling students to make career decisions based on the latest information. In addition, it is equipped with artificial intelligence that analyzes students' hobbies and value systems, and proposes the optimal career path for each individual student, thereby supporting students' career choices while reducing the burden on educational institutions.

[0006] "Information processing means" refers to a device or method that performs calculations and judgments for career support based on student input information.

[0007] "Presentation means" refers to a function or method of visually or audibly showing advice generated by information processing means to the user.

[0008] "Means of collecting feedback" refers to a function or method for recording opinions and impressions regarding advice provided by users.

[0009] A "database" is a collection of information that stores collected feedback and historical data, and can be searched and referenced as needed.

[0010] "Industry trend information" refers to information about recent changes and future predictions in a specific industry.

[0011] "Required skills information" refers to information about the skills and abilities required in a particular occupation or industry.

[0012] Artificial intelligence is a technology in which computer systems mimic specific aspects of human intelligence to perform data analysis and decision-making.

[0013] A "career path" refers to a series of steps or choices related to an individual's occupation, and is the roadmap by which that person shapes their professional life. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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 a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] 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.

[0019] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] 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).

[0021] 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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] This invention is a system that appropriately provides students with the information they need when choosing their career path and offers career support based on their individual values. This system is designed so that the three roles of server, terminal, and user work in coordination.

[0036] First, users access the platform via their smartphone or PC and log in. During login, the server processes the user's authentication information and verifies it against the database. Once authentication is approved, users can select options such as career counseling, mock interviews, and resume review.

[0037] When a user selects a desired service, the device displays a corresponding set of questions. These questions are dynamically generated by the server and are designed to gather information about the user's interests, values, and past performance. Once the user answers the questions, the information is sent to the server, where artificial intelligence further analyzes this data.

[0038] The server's artificial intelligence evaluates diverse career paths based on the user's characteristics and generates advice including appropriate job types, industry trends, and necessary skills. The generated advice is presented to the user via a terminal, and the user can provide feedback on its content. This feedback is collected by the server and used to improve future decision-making and suggestions.

[0039] To give a concrete example, suppose a user asks for advice saying, "I'm interested in design, but I don't know how to build a career in it." The device displays relevant questions and focuses on the user's values ​​and skills. The server analyzes the answers and provides advice that includes design industry trends, necessary skills, and appropriate learning resources. Based on this information, the user can plan their career.

[0040] A key feature of this system is that the advice provided to each user is highly personalized, as it is generated by combining the latest industry information with the user's individual characteristics. Furthermore, it boasts an advice algorithm that constantly evolves through a feedback loop. This allows the system to provide powerful support for students to make career choices they won't regret.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] Users access the platform using their smartphones or PCs and display the login screen. They then enter their email address and password to log in.

[0044] Step 2:

[0045] The terminal sends the entered authentication information to the server. The server compares the received authentication information with the database to verify that the user is legitimate. If authentication is successful, the server generates a session ID and sends an authentication success response to the terminal.

[0046] Step 3:

[0047] The terminal receives a successful authentication response from the server and displays a menu screen to the user that includes options such as career counseling, mock interviews, and document review. The user selects the service they wish to use.

[0048] Step 4:

[0049] The terminal sends the user's selection to the server. Based on the user's selection, the server dynamically generates an appropriate set of questions and sends them to the terminal.

[0050] Step 5:

[0051] The terminal displays a set of questions received from the server to the user and prompts the user to input information about their hobbies, values, and academic performance. The user then enters the necessary information based on the presented questions.

[0052] Step 6:

[0053] The terminal sends the user's input information to the server. The server passes the received data to artificial intelligence and begins the analysis process.

[0054] Step 7:

[0055] The server's artificial intelligence analyzes user data and generates career advice, including appropriate job roles, skills, and trends, based on the user's characteristics and industry trends. This advice is personalized according to the user's characteristics.

[0056] Step 8:

[0057] The server sends the generated carrier advice to the device. The device displays the received advice to the user. The user has the option to review the advice and provide feedback.

[0058] Step 9:

[0059] Users input feedback on the advice and send it to the server via their device. The server stores the received feedback in a database and uses it to improve future suggestion algorithms.

[0060] Step 10:

[0061] The server terminates the user's session and performs the logout procedure as needed. The terminal refreshes its screen and displays the user the login screen or menu screen.

[0062] (Example 1)

[0063] 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."

[0064] Many students face the challenge of finding a suitable career path based on their hobbies and values. Furthermore, career choices need to be based on the latest information, taking into account rapidly changing industry trends, but efficiently providing this information and offering personalized advice is difficult.

[0065] 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.

[0066] In this invention, the server includes means for verifying the user's authentication information, means for generating and presenting a set of questions corresponding to the service selected by the user, and means for using a generative AI model to analyze the user's response information and propose an appropriate career path. This makes it possible to provide personalized career advice based on the individual characteristics of the user.

[0067] "Authentication information" refers to the identification information necessary for a user to access the system, and includes things like usernames and passwords.

[0068] "Services" refer to options that users can select through the system, such as career counseling, mock interviews, and resume / document review.

[0069] A "question set" is a series of questions provided by the server to analyze user characteristics, designed to collect data on hobbies, values, and academic performance.

[0070] A "generative AI model" is an artificial intelligence technology used to analyze user response data and propose career paths based on individual characteristics.

[0071] A "career path" refers to the career or industry a user aspires to work in, and includes the necessary skills and experience to achieve it.

[0072] "Feedback" refers to the act of a user sending their opinions and evaluations of the information and advice provided to the server, which is used to improve the system and adjust the advice.

[0073] "Information storage means" refers to technologies such as databases for storing user feedback and historical data.

[0074] The embodiments for carrying out the present invention will be described in detail. The invention provides personalized career support to students and other users using an information processing system. The system overview and specific operation will be described below.

[0075] First, users access the system through devices such as PCs or smartphones. Users enter their authentication information on the login screen, and the server verifies this information against a database to perform authentication. Next, if authentication is successful, the user can access the service menu.

[0076] The service menu allows users to select options such as career counseling, mock interviews, and resume review. Depending on the selected service, the server dynamically generates a specific set of questions and sends them to the user's device. These questions are intended to gather information about the user's hobbies, values, past academic performance, and other relevant details.

[0077] When a user answers a question, the device sends this data to a server. The server uses a generative AI model to analyze the collected data and evaluate the optimal career path for the user. The AI ​​model operates based on prompts such as, "Please suggest the steps necessary for the user to pursue a design career." Based on the analysis, the server generates detailed advice including industry trends, required skills, and learning resources.

[0078] The generated advice is then presented to the user again via the terminal. The user can provide feedback on the content, and this feedback is stored on the server. The server can then use this feedback to improve future advice generation. For example, if a user asks, "I'm thinking of entering the medical industry, which qualifications would be advantageous?", the server will use an AI model to suggest specific methods for obtaining qualifications and relevant skills.

[0079] In this way, the system of the present invention can continue to provide users with personalized career support that reflects the latest information.

[0080] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0081] Step 1:

[0082] The user accesses the system using a terminal and enters authentication information on the login screen. The entered authentication information is sent from the terminal to the server. The server compares this information with data stored in the database to determine its authenticity. If authentication is successful, an approval message is returned to the terminal, and the user can proceed to the next step.

[0083] Step 2:

[0084] The server generates a service menu for approved users and sends it to their terminal. The user selects their desired service from options such as career counseling, mock interviews, and document review via their terminal. The user's selection information is then sent back to the server. The server receives this information and prepares for the next processing step.

[0085] Step 3:

[0086] The server dynamically generates a specific set of questions based on the service selected by the user. The generated set of questions is sent to the terminal and presented to the user. The generation of the question set takes into account the user's past history and certain industry trends.

[0087] Step 4:

[0088] The user answers questions displayed on the device and submits their answers. The device sends this answer data to the server. The server inputs the received data into a generating AI model and performs data analysis. The results of the analysis are used to generate advice later.

[0089] Step 5:

[0090] The server uses a generative AI model to analyze user response data. Specifically, it analyzes the user's hobbies, value system, and industry needs using prompt sentences, and then evaluates the optimal career path based on this. This analysis generates information on the necessary skills and learning resources.

[0091] Step 6:

[0092] The server sends the generated carrier information and advice to the terminal and presents it to the user. The user reviews this advice and provides feedback as needed. After feedback is submitted, that information is sent from the terminal to the server.

[0093] Step 7:

[0094] The server stores user feedback in its data storage system. This feedback is used as data to help generate advice and improve the system in the future. By analyzing the feedback and incorporating it into improvements to the generated AI model, the server can provide more accurate advice.

[0095] (Application Example 1)

[0096] 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."

[0097] Traditional career support systems have faced challenges in providing direct and immediate feedback and consultation to individual students, resulting in insufficient personalized information delivery. Furthermore, there is a lack of career advice based on real-world experience, and support for students in envisioning concrete future career paths is inadequate.

[0098] 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.

[0099] In this invention, the server includes an information processing means for providing career support based on student input information, a presentation means for presenting advice generated by the information processing means, and a means for directly interacting with the student in the real world while presenting the advice via a glasses-type device. This makes it possible to provide students with immediate, personalized career advice.

[0100] "Student input information" refers to data obtained from students regarding their personal interests, values, experiences, and academic performance related to their career paths and paths.

[0101] "Career support" refers to activities that provide students with the information, advice, and guidance they need when making future career choices.

[0102] "Information processing means" refers to a device or software that generates analysis and appropriate advice based on collected input information from students.

[0103] "Presentation means" refers to a device or interface for displaying or notifying students of the generated advice.

[0104] "Means of collecting feedback" refers to a device or function for obtaining students' opinions and evaluations of the advice they receive.

[0105] "Data storage means" refers to a database or storage device for storing collected feedback and student history data.

[0106] "A means of direct interaction in the real world while providing advice via a glasses-type device" refers to a method of meeting with students face-to-face using a glasses-type wearable device and providing career advice in real time.

[0107] "Industry trend information" refers to data and knowledge about the latest trends and changes in a specific industry.

[0108] "Required technical information" refers to information about the skills and technologies required for a particular occupation or industry.

[0109] "Interests and value systems" refer to the objects of interest and the set of standards and beliefs that each student considers important in life.

[0110] In this invention, the system involves a server, terminals, and users each fulfilling their respective roles and functioning in coordination. The server processes student input information and generates appropriate career support advice. The terminals, such as smartphones and personal computers, serve as the medium for presenting the generated advice. Furthermore, by utilizing glasses-type devices, direct interaction with the user in the real world is possible, enabling immediate feedback.

[0111] Specifically, a person wears a glasses-type device (e.g., smart glasses) and displays questions to students face-to-face, allowing them to input their answers in real time. The server collects the received answers in real time through devices such as Google Glass® and analyzes them using an AI model (e.g., a generative AI model using TENSORFLOW®). Based on the analysis, the server generates advice on the most suitable career path for the student, which is then visually presented to the user through the glasses-type device.

[0112] As a concrete example of this system, consider a scenario where a high school student meets with a specialist wearing glasses and asks, "I want to become an engineer, what kind of preparation do I need?" Based on the information gathered in this situation, the server generates and presents engineer-oriented advice, including appropriate university courses, necessary skill sets, and the latest industry trends.

[0113] An example of a prompt to input into the generating AI model is, "Please tell me how to provide appropriate career advice to a high school student aspiring to be an engineer, based on the user's interests and skills." This allows for highly personalized career support to be provided to the user, along with concrete, actionable steps.

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

[0115] Step 1:

[0116] The user wears a glasses-type device and logs into the terminal for carrier consultation.

[0117] In this process, the user enters personal information and interests, and this information is sent from the device to the server.

[0118] Based on the input information, the server uses an AI model to analyze data related to the user's interests and past performance.

[0119] The analysis output is a set of questions based on the user's interests and value system.

[0120] Step 2:

[0121] The server sends the generated set of questions to the glasses-type device via the terminal and displays them to the user.

[0122] The user answers questions through smart glasses.

[0123] User responses are entered into the terminal in real time and sent back to the server.

[0124] The server uses the input data to perform analysis using an AI model and calculates the data to determine the appropriate career path for the user.

[0125] Step 3:

[0126] The server presents advice generated by the AI ​​model to the user through a glasses-type device.

[0127] This advice is personalized and includes industry trend information and necessary technical information.

[0128] After the information is presented, users can ask additional questions or provide feedback.

[0129] Feedback is sent to the server via the device and used to improve future advice.

[0130] Step 4:

[0131] The server stores the collected feedback and user history in a data storage device.

[0132] This helps improve the accuracy of future advice and enhances our services.

[0133] The saved data will be used during new user sessions, contributing to an improved user experience.

[0134] 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.

[0135] This invention is a system that provides career support based on student input information, and in particular, incorporates an emotion engine to provide advice that takes the user's emotions into consideration. This system consists of three main components: a server, a terminal, and a user.

[0136] First, the user accesses the platform using their device and logs in. The user enters their authentication information, which the server then uses to verify the user's legitimacy by comparing it against the database. Once logged in, the device presents the user with options such as career counseling, mock interviews, and resume review.

[0137] When a user selects a desired service, the device notifies the server. The server generates a set of questions based on the user's selections, which may include questions for sentiment analysis. The set of questions is presented to the user via the device, and the user answers them. At this time, the device has an emotion engine built in to measure the user's emotional state, analyzing facial expressions, voice, and behavioral patterns during input to infer the user's emotions.

[0138] The server receives user response data and sentiment data collected from the terminal and has artificial intelligence analyze this data. Based on the response data and sentiment data, the AI ​​generates career advice that is best suited to the user's personality. This advice is customized not only with industry trend information and required skills information, but also with content that is best suited to the user's emotional state.

[0139] The generated advice is sent to the terminal via the server and presented to the user. When presenting the advice, the terminal analyzes the user's facial expressions and reactions using an emotion engine, collecting real-time feedback based on emotional changes. This allows the server to accumulate data that further optimizes the advice generation process.

[0140] As a concrete example, suppose a user asks for advice because they are interested in international relations but are unsure of a suitable career path. The device presents the user with a series of related questions, and in the process, transmits emotional data recognized by the emotion engine. Based on this, the server customizes and presents advice that incorporates the latest trends in international relations, specific skills, and elements that are likely to motivate the user.

[0141] By using an emotional engine in conjunction with traditional career advice, it becomes possible to provide support that is more attentive to the user and tailored to their individual condition and emotions.

[0142] The following describes the processing flow.

[0143] Step 1:

[0144] Users access the platform using their smartphones or PCs and are directed to the login screen. They then enter their email address and password to log in.

[0145] Step 2:

[0146] The terminal sends the entered authentication information to the server. The server compares the received authentication information with the database to verify that the user is legitimate. If authentication is successful, the server generates a session ID and sends an authentication success response to the terminal.

[0147] Step 3:

[0148] The terminal receives a successful authentication response from the server and displays a menu screen to the user that includes options such as career counseling, mock interviews, and document review. The user selects the service they wish to use.

[0149] Step 4:

[0150] The terminal sends the user's selection to the server. Based on the user's selection, the server dynamically generates an appropriate set of questions and sends them to the terminal. This set of questions also includes questions for sentiment analysis.

[0151] Step 5:

[0152] The terminal displays a set of questions received from the server to the user, prompting them to provide input about their hobbies, values, academic performance, and emotions. While the user answers the questions for emotion analysis, the emotion engine built into the terminal senses the user's facial expressions and voice, and collects emotion data.

[0153] Step 6:

[0154] The device sends the user's response data and sentiment data to the server. The server passes the received data to artificial intelligence and begins the analysis process.

[0155] Step 7:

[0156] The server's artificial intelligence analyzes user response data and sentiment data to generate career advice that takes into account user characteristics, industry trends, and factors that tend to motivate the user. This advice is customized and highly personalized based on the sentiment data.

[0157] Step 8:

[0158] The server sends the generated career advice to the device. The device displays the received advice to the user. During presentation, the device's emotion engine analyzes the user's facial expressions and reactions in real time and collects data on emotional changes.

[0159] Step 9:

[0160] Users input feedback on the advice and send it to the server via their device. The server stores the feedback and sentiment data in a database to help improve the advice generation process in the future.

[0161] Step 10:

[0162] The server terminates the user's session and performs the logout procedure as needed. The terminal refreshes its screen and displays the user the login screen or menu screen.

[0163] (Example 2)

[0164] 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".

[0165] In modern career support, there is a need to address the individual needs of students and provide more appropriate advice. However, conventional systems do not adequately customize advice to reflect students' emotional states, and a more flexible and individualized system is needed. In particular, there is a lack of career guidance that is attentive to the anxieties and hopes that students feel, so new technologies are needed to generate advice that takes emotions into account.

[0166] 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.

[0167] In this invention, the server includes an information processing means for providing career support based on student input information, a presentation means for presenting generated advice, and a means for analyzing the user's emotions and customizing the advice based on that data. This enables highly accurate career advice tailored to the student's personality and emotional state.

[0168] "Information processing means" refers to means that perform data processing based on input information from students and have the function of providing necessary career support.

[0169] "Presentation means" refers to means that have the function of providing advice generated by information processing means to the user through visual or auditory means.

[0170] A "means for collecting feedback" refers to a means that has the function of collecting the reactions and opinions that users have given to the advice they have received.

[0171] A "database" is an information management system that stores collected feedback and historical data, and allows for searching and updating as needed.

[0172] A "means for analyzing emotions" refers to a means that has the function of inferring the emotional state from the user's facial expressions, voice, and input patterns, and acquiring that data.

[0173] A "generative AI model" is an artificial intelligence model that analyzes patterns based on input data and generates information optimized for the user.

[0174] "Means of customization" refers to a means of adjusting and modifying the advice generated based on collected emotional data to suit the individual needs of the user.

[0175] This invention provides a system for efficiently supporting students' career development. The system mainly consists of three main components: a server, a terminal, and a user.

[0176] The server is equipped with information processing capabilities and performs data processing necessary for career support based on input information from students. Specifically, the server uses a generative AI model to analyze the input data and generate optimal career advice. The server also works in conjunction with a database to accumulate feedback and historical data, which will be used to generate more precise advice in the future.

[0177] The terminal is a device for users to interact with the system and is equipped with presentation and emotion analysis capabilities. The terminal presents advice sent from the server to the user through a visual interface. The emotion analysis capabilities installed in the terminal analyze the user's facial expressions and voice in real time and collect emotion data. This emotion data is sent to the server and used to customize the advice.

[0178] Users access the platform via their devices and log in by entering their authentication information. After logging in, users select services such as career counseling, mock interviews, and document review, and answer questions based on those services. The user's responses and behavioral patterns are collected as emotional data through sentiment analysis.

[0179] For example, if a user asks for advice because they are interested in international relations but are unsure of a suitable career path, relevant questions are presented, and emotional data is collected along with the answers. The server inputs this data into a generating AI model to produce advice that includes the latest industry trends and necessary skills. This advice is then presented on the user's device as the most appropriate response to their emotional state.

[0180] As an example of a prompt, you can input instructions to the AI ​​model in the form of, "Generate optimal career advice for a student interested in international relations, taking into account their emotional state."

[0181] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0182] Step 1:

[0183] The user accesses the platform using their device and enters their authentication information on the login screen. The device sends the entered user ID and password to the server. The server authenticates the user by comparing it with the database and, after confirming its legitimacy, starts the user session. If authentication is successful, the server outputs a login success status to the device.

[0184] Step 2:

[0185] Once a user successfully logs in, the server generates service options based on the user's profile information (e.g., career counseling, mock interviews, resume review) and sends them to the terminal. The terminal visually displays the generated options to the user. The user selects the desired service from the presented options and sends it to the terminal as input. The terminal then sends the selected service information back to the server, and the process proceeds to the next step as output.

[0186] Step 3:

[0187] Based on the user's selection, the server begins data processing to generate the appropriate set of questions. This set of questions may include items to analyze the user's emotions, if necessary. The server creates the set of questions from the input data and sends it to the terminal. The terminal then presents the generated set of questions to the user.

[0188] Step 4:

[0189] The user answers questions through the device. The device uses its built-in sentiment analysis engine to analyze the user's facial expressions, voice, and behavioral patterns during input in real time, and acquires sentiment data. The response data and sentiment data are sent to the server through the device. The server receives this data as output for the next processing step.

[0190] Step 5:

[0191] The server inputs the received response data and sentiment data into a generating AI model. This AI model analyzes the input data and generates optimal career advice for the user. As output, the AI ​​model generates customized advice that takes into account factors such as industry trends, required skills, and the user's emotional state. This is then sent to the terminal.

[0192] Step 6:

[0193] The device presents the user with customized advice sent from the server. Upon presentation, the device again uses its emotion analysis engine to analyze the user's real-time facial expressions and reactions, obtaining feedback data. This feedback data is sent to the server via the device and stored as output to help improve future analysis accuracy.

[0194] (Application Example 2)

[0195] 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".

[0196] Food delivery users often find it difficult to make the right choice due to the wide variety of options available. Furthermore, few services offer personalized recommendations based on the user's emotional state. Addressing these issues and providing an optimal food delivery experience tailored to individual needs is crucial.

[0197] 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.

[0198] In this invention, the server includes an information processing means for providing advisory support based on user input information, a display means for presenting recommendations generated by the information processing means, and a means for collecting the user's response to the displayed recommendations after the recommendations generated based on the emotional state detected by the emotion evaluation means have been presented. This enables personalized food delivery selection according to the user's emotional state.

[0199] A "user" is an individual who uses the system to receive food delivery or other services.

[0200] "Input information" refers to a collection of data about the choices and requests that users provide to the system.

[0201] "Advisory support" is a process of providing suggestions and advice to help users make better choices.

[0202] "Information processing means" refers to a technical device or program that performs computational processing to generate recommendations based on input information.

[0203] "Display means" refers to devices or methods for presenting generated recommendations to users visually or audibly.

[0204] "Emotional evaluation means" refers to a technical device or method for evaluating a user's emotional state, often using devices such as cameras or microphones.

[0205] "Means for collecting responses" refers to technical methods or devices for collecting and analyzing user responses to displayed recommendations.

[0206] A "memory device" is a data storage medium or system used to store reaction and historical data.

[0207] A description of the embodiment for carrying out the invention will be provided.

[0208] This system is designed to provide personalized advice to users based on their emotional state during food delivery. The system works as follows:

[0209] First, the terminal receives input information from the user. At this stage, the user enters their preferences and desired type of cuisine into the terminal. The terminal is equipped with a camera and microphone, and through these devices, it acquires the user's facial expressions and voice data. This data is analyzed in real time by an emotion evaluation system. This analysis uses an emotion analysis library built in Python and the Google Cloud Speech-to-Text API.

[0210] Next, the server receives input information and emotional data sent from the terminal. Within the server, information processing tools generate food delivery options suitable for the user. This selection is based on the user's emotional state and past history, determining the most appropriate recommended menu for the user.

[0211] Finally, the selected recommended menu is presented to the user on their device through a display mechanism. The server then collects user response data and records it in storage. This data is used for further personalization in future visits.

[0212] For example, if a user is complaining of fatigue, this system can recommend comforting foods, such as soothing soups or relaxing teas. An example of a prompt from the generative AI model used would be, "Suggest relaxing food items based on the user's emotional state."

[0213] In this way, the system can provide a more personalized food delivery experience that is attentive to the user's emotions.

[0214] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0215] Step 1:

[0216] The terminal receives user input information, including the user's preferred cuisine type and allergy information. The terminal then centralizes this information and converts it into a format for transmission to the server. This clarifies the user's preferences and requirements.

[0217] Step 2:

[0218] The device uses its camera and microphone to capture the user's facial expressions and voice data. This data is essential for analysis by emotion assessment tools. Image processing and speech recognition technologies are used for the analysis, and the results are output as numerical data to identify the user's emotional state. This data is temporarily stored on the device.

[0219] Step 3:

[0220] The server receives input information and emotional data transmitted from the terminal. This data is analyzed by information processing tools operating within the server. Specifically, a machine learning algorithm is implemented to combine the user's preference patterns and emotional states. The algorithm utilizes past usage history and emotional data to generate recommendations for the most suitable dishes. This result is output as a recommended menu list.

[0221] Step 4:

[0222] The server sends the generated recommended menu to the terminal. The terminal displays the recommended menu to the user using a display device. The user reviews this and uses it to decide on their order. At this time, the user can also view detailed information about the menu provided on the terminal (price, nutritional information, etc.).

[0223] Step 5:

[0224] After the user views the recommended menu, the device uses its camera and microphone again to record the user's reactions. This allows for sentiment analysis of the user's reactions to the presented recommendations. The analyzed data is sent via the device to a server and stored in its storage device.

[0225] Step 6:

[0226] The server analyzes stored user response data and updates its machine learning model to reflect this in future recommendations. This continuous analysis and data feedback loop allows the system to improve accuracy over time. As a result, future recommendations become more personalized, providing users with the best possible choices.

[0227] 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.

[0228] 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.

[0229] 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.

[0230] [Second Embodiment]

[0231] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0232] 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.

[0233] 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).

[0234] 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.

[0235] 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.

[0236] 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).

[0237] 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.

[0238] 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.

[0239] 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.

[0240] 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.

[0241] 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.

[0242] 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".

[0243] This invention is a system that appropriately provides students with the information they need when choosing their career path and offers career support based on their individual values. This system is designed so that the three roles of server, terminal, and user work in coordination.

[0244] First, users access the platform via their smartphone or PC and log in. During login, the server processes the user's authentication information and verifies it against the database. Once authentication is approved, users can select options such as career counseling, mock interviews, and resume review.

[0245] When a user selects a desired service, the device displays a corresponding set of questions. These questions are dynamically generated by the server and are designed to gather information about the user's interests, values, and past performance. Once the user answers the questions, the information is sent to the server, where artificial intelligence further analyzes this data.

[0246] The server's artificial intelligence evaluates diverse career paths based on the user's characteristics and generates advice including appropriate job types, industry trends, and necessary skills. The generated advice is presented to the user via a terminal, and the user can provide feedback on its content. This feedback is collected by the server and used to improve future decision-making and suggestions.

[0247] To give a concrete example, suppose a user asks for advice saying, "I'm interested in design, but I don't know how to build a career in it." The device displays relevant questions and focuses on the user's values ​​and skills. The server analyzes the answers and provides advice that includes design industry trends, necessary skills, and appropriate learning resources. Based on this information, the user can plan their career.

[0248] A key feature of this system is that the advice provided to each user is highly personalized, as it is generated by combining the latest industry information with the user's individual characteristics. Furthermore, it boasts an advice algorithm that constantly evolves through a feedback loop. This allows the system to provide powerful support for students to make career choices they won't regret.

[0249] The following describes the processing flow.

[0250] Step 1:

[0251] Users access the platform using their smartphones or PCs and display the login screen. They then enter their email address and password to log in.

[0252] Step 2:

[0253] The terminal sends the entered authentication information to the server. The server compares the received authentication information with the database to verify that the user is legitimate. If authentication is successful, the server generates a session ID and sends an authentication success response to the terminal.

[0254] Step 3:

[0255] The terminal receives a successful authentication response from the server and displays a menu screen to the user that includes options such as career counseling, mock interviews, and document review. The user selects the service they wish to use.

[0256] Step 4:

[0257] The terminal sends the user's selection to the server. Based on the user's selection, the server dynamically generates an appropriate set of questions and sends them to the terminal.

[0258] Step 5:

[0259] The terminal displays a set of questions received from the server to the user and prompts the user to input information about their hobbies, values, and academic performance. The user then enters the necessary information based on the presented questions.

[0260] Step 6:

[0261] The terminal sends the user's input information to the server. The server passes the received data to artificial intelligence and begins the analysis process.

[0262] Step 7:

[0263] The server's artificial intelligence analyzes user data and generates career advice, including appropriate job roles, skills, and trends, based on the user's characteristics and industry trends. This advice is personalized according to the user's characteristics.

[0264] Step 8:

[0265] The server sends the generated carrier advice to the device. The device displays the received advice to the user. The user has the option to review the advice and provide feedback.

[0266] Step 9:

[0267] Users input feedback on the advice and send it to the server via their device. The server stores the received feedback in a database and uses it to improve future suggestion algorithms.

[0268] Step 10:

[0269] The server terminates the user's session and performs the logout procedure as needed. The terminal refreshes its screen and displays the user the login screen or menu screen.

[0270] (Example 1)

[0271] 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."

[0272] Many students face the challenge of finding a suitable career path based on their hobbies and values. Furthermore, career choices need to be based on the latest information, taking into account rapidly changing industry trends, but efficiently providing this information and offering personalized advice is difficult.

[0273] 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.

[0274] In this invention, the server includes means for verifying the user's authentication information, means for generating and presenting a set of questions corresponding to the service selected by the user, and means for using a generative AI model to analyze the user's response information and propose an appropriate career path. This makes it possible to provide personalized career advice based on the individual characteristics of the user.

[0275] "Authentication information" refers to the identification information necessary for a user to access the system, and includes things like usernames and passwords.

[0276] "Services" refer to options that users can select through the system, such as career counseling, mock interviews, and resume / document review.

[0277] A "question set" is a series of questions provided by the server to analyze user characteristics, designed to collect data on hobbies, values, and academic performance.

[0278] A "generative AI model" is an artificial intelligence technology used to analyze user response data and propose career paths based on individual characteristics.

[0279] A "career path" refers to the career or industry a user aspires to work in, and includes the necessary skills and experience to achieve it.

[0280] "Feedback" refers to the act of a user sending their opinions and evaluations of the information and advice provided to the server, which is used to improve the system and adjust the advice.

[0281] "Information storage means" refers to technologies such as databases for storing user feedback and historical data.

[0282] The embodiments for implementing the present invention will be described in detail. The invention provides individualized career support for students and other users using an information processing system. The following will explain the overview and specific operations of the system.

[0283] First, the user accesses the system through a terminal such as a PC or smartphone. The user inputs authentication information on the login screen, and the server verifies the information against the database to perform authentication. Next, upon successful authentication, the user can access the service menu.

[0284] In the service menu, the user can select options such as career counseling, mock interviews, and document review. Depending on the selected service, the server dynamically generates a specific set of questions and sends them to the user's terminal. These questions aim to collect information about the user's hobbies, values, past achievements, etc.

[0285] When the user answers the questions, the terminal sends this data to the server. The server uses a generated AI model to analyze the collected data and evaluate the optimal career path for the user. The AI model operates based on prompt texts such as "Please propose the steps necessary for the user to aim for a design job." As a result of the analysis, the server generates detailed advice including industry trends, required skills, learning resources, etc.

[0286] The generated advice is presented to the user again through the terminal. The user can provide feedback on the content, and this feedback is saved on the server. Subsequently, the server can use the feedback to improve future advice generation. For example, when a user asks a question such as "I am considering entering the medical industry. Which qualifications are advantageous?", the server uses the AI model to present specific methods of obtaining qualifications and related skills.

[0287] In this way, the system of the present invention can continue to provide users with personalized career support that reflects the latest information.

[0288] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0289] Step 1:

[0290] The user accesses the system using a terminal and enters authentication information on the login screen. The entered authentication information is sent from the terminal to the server. The server compares this information with data stored in the database to determine its authenticity. If authentication is successful, an approval message is returned to the terminal, and the user can proceed to the next step.

[0291] Step 2:

[0292] The server generates a service menu for approved users and sends it to their terminal. The user selects their desired service from options such as career counseling, mock interviews, and document review via their terminal. The user's selection information is then sent back to the server. The server receives this information and prepares for the next processing step.

[0293] Step 3:

[0294] The server dynamically generates a specific set of questions based on the service selected by the user. The generated set of questions is sent to the terminal and presented to the user. The generation of the question set takes into account the user's past history and certain industry trends.

[0295] Step 4:

[0296] The user answers questions displayed on the device and submits their answers. The device sends this answer data to the server. The server inputs the received data into a generating AI model and performs data analysis. The results of the analysis are used to generate advice later.

[0297] Step 5:

[0298] The server uses a generative AI model to analyze user response data. Specifically, it analyzes the user's hobbies, value system, and industry needs using prompt sentences, and then evaluates the optimal career path based on this. This analysis generates information on the necessary skills and learning resources.

[0299] Step 6:

[0300] The server sends the generated carrier information and advice to the terminal and presents it to the user. The user reviews this advice and provides feedback as needed. After feedback is submitted, that information is sent from the terminal to the server.

[0301] Step 7:

[0302] The server stores user feedback in its data storage system. This feedback is used as data to help generate advice and improve the system in the future. By analyzing the feedback and incorporating it into improvements to the generated AI model, the server can provide more accurate advice.

[0303] (Application Example 1)

[0304] 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."

[0305] Traditional career support systems have faced challenges in providing direct and immediate feedback and consultation to individual students, resulting in insufficient personalized information delivery. Furthermore, there is a lack of career advice based on real-world experience, and support for students in envisioning concrete future career paths is inadequate.

[0306] 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.

[0307] In this invention, the server includes information processing means for providing career support based on the input information of students, presenting means for presenting the advice generated by the information processing means, and means for directly interacting in the real world while presenting the advice via a glasses-type device. This enables the provision of immediate personalized career advice to students.

[0308] The "input information of students" refers to data such as a student's course of study, personal interests, values, experiences, and academic achievements obtained from the student and related to career paths.

[0309] "Career support" refers to activities that provide information, advice, and guidance necessary for students when making future career choices.

[0310] The "information processing means" is a device or software for generating analysis and appropriate advice based on the collected input information of students.

[0311] The "presenting means" is a device or interface for displaying or notifying the generated advice to students.

[0312] The "means for collecting feedback" is a device or function for obtaining opinions and evaluations on the advice provided to students.

[0313] The "data storage means" is a database or storage device for storing the collected feedback and the historical data of students.

[0314] The "means for directly interacting in the real world while presenting advice via a glasses-type device" is a means for providing career advice to students in real time while facing the students using a glasses-type wearable device.

[0315] The "industry trend information" refers to data and knowledge regarding the latest trends and changes in a specific industry.

[0316] "Required technical information" refers to information about the skills and technologies required for a particular occupation or industry.

[0317] "Interests and value systems" refer to the objects of interest and the set of standards and beliefs that each student considers important in life.

[0318] In this invention, the system involves a server, terminals, and users each fulfilling their respective roles and functioning in coordination. The server processes student input information and generates appropriate career support advice. The terminals, such as smartphones and personal computers, serve as the medium for presenting the generated advice. Furthermore, by utilizing glasses-type devices, direct interaction with the user in the real world is possible, enabling immediate feedback.

[0319] Specifically, a person wears a glasses-type device (e.g., smart glasses) and displays questions to students face-to-face, allowing them to input their answers in real time. The server collects the received answers in real time through a device such as Google Glass and analyzes them using an AI model (e.g., a generative AI model using TensorFlow). Based on the analysis, the server generates advice on the most suitable career path for the student, which is then visually presented to the user through the glasses-type device.

[0320] As a concrete example of this system, consider a scenario where a high school student meets with a specialist wearing glasses and asks, "I want to become an engineer, what kind of preparation do I need?" Based on the information gathered in this situation, the server generates and presents engineer-oriented advice, including appropriate university courses, necessary skill sets, and the latest industry trends.

[0321] An example of a prompt to input into the generating AI model is, "Please tell me how to provide appropriate career advice to a high school student aspiring to be an engineer, based on the user's interests and skills." This allows for highly personalized career support to be provided to the user, along with concrete, actionable steps.

[0322] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0323] Step 1:

[0324] The user wears a glasses-type device and logs into the terminal for carrier consultation.

[0325] In this process, the user enters personal information and interests, and this information is sent from the device to the server.

[0326] Based on the input information, the server uses an AI model to analyze data related to the user's interests and past performance.

[0327] The analysis output is a set of questions based on the user's interests and value system.

[0328] Step 2:

[0329] The server sends the generated set of questions to the glasses-type device via the terminal and displays them to the user.

[0330] The user answers questions through smart glasses.

[0331] User responses are entered into the terminal in real time and sent back to the server.

[0332] The server uses the input data to perform analysis using an AI model and calculates the data to determine the appropriate career path for the user.

[0333] Step 3:

[0334] The server presents advice generated by the AI ​​model to the user through a glasses-type device.

[0335] This advice is personalized and includes industry trend information and necessary technical information.

[0336] After the information is presented, users can ask additional questions or provide feedback.

[0337] Feedback is sent to the server via the device and used to improve future advice.

[0338] Step 4:

[0339] The server stores the collected feedback and user history in a data storage device.

[0340] This helps improve the accuracy of future advice and enhances our services.

[0341] The saved data will be used during new user sessions, contributing to an improved user experience.

[0342] 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.

[0343] This invention is a system that provides career support based on student input information, and in particular, incorporates an emotion engine to provide advice that takes the user's emotions into consideration. This system consists of three main components: a server, a terminal, and a user.

[0344] First, the user accesses the platform using their device and logs in. The user enters their authentication information, which the server then uses to verify the user's legitimacy by comparing it against the database. Once logged in, the device presents the user with options such as career counseling, mock interviews, and resume review.

[0345] When a user selects a desired service, the device notifies the server. The server generates a set of questions based on the user's selections, which may include questions for sentiment analysis. The set of questions is presented to the user via the device, and the user answers them. At this time, the device has an emotion engine built in to measure the user's emotional state, analyzing facial expressions, voice, and behavioral patterns during input to infer the user's emotions.

[0346] The server receives user response data and sentiment data collected from the terminal and has artificial intelligence analyze this data. Based on the response data and sentiment data, the AI ​​generates career advice that is best suited to the user's personality. This advice is customized not only with industry trend information and required skills information, but also with content that is best suited to the user's emotional state.

[0347] The generated advice is sent to the terminal via the server and presented to the user. When presenting the advice, the terminal analyzes the user's facial expressions and reactions using an emotion engine, collecting real-time feedback based on emotional changes. This allows the server to accumulate data that further optimizes the advice generation process.

[0348] As a concrete example, suppose a user asks for advice because they are interested in international relations but are unsure of a suitable career path. The device presents the user with a series of related questions, and in the process, transmits emotional data recognized by the emotion engine. Based on this, the server customizes and presents advice that incorporates the latest trends in international relations, specific skills, and elements that are likely to motivate the user.

[0349] By using an emotional engine in conjunction with traditional career advice, it becomes possible to provide support that is more attentive to the user and tailored to their individual condition and emotions.

[0350] The following describes the processing flow.

[0351] Step 1:

[0352] Users access the platform using their smartphones or PCs and are directed to the login screen. They then enter their email address and password to log in.

[0353] Step 2:

[0354] The terminal sends the entered authentication information to the server. The server compares the received authentication information with the database to verify that the user is legitimate. If authentication is successful, the server generates a session ID and sends an authentication success response to the terminal.

[0355] Step 3:

[0356] The terminal receives a successful authentication response from the server and displays a menu screen to the user that includes options such as career counseling, mock interviews, and document review. The user selects the service they wish to use.

[0357] Step 4:

[0358] The terminal sends the user's selection to the server. Based on the user's selection, the server dynamically generates an appropriate set of questions and sends them to the terminal. This set of questions also includes questions for sentiment analysis.

[0359] Step 5:

[0360] The terminal displays a set of questions received from the server to the user, prompting them to provide input about their hobbies, values, academic performance, and emotions. While the user answers the questions for emotion analysis, the emotion engine built into the terminal senses the user's facial expressions and voice, and collects emotion data.

[0361] Step 6:

[0362] The device sends the user's response data and sentiment data to the server. The server passes the received data to artificial intelligence and begins the analysis process.

[0363] Step 7:

[0364] The server's artificial intelligence analyzes user response data and sentiment data to generate career advice that takes into account user characteristics, industry trends, and factors that tend to motivate the user. This advice is customized and highly personalized based on the sentiment data.

[0365] Step 8:

[0366] The server sends the generated career advice to the device. The device displays the received advice to the user. During presentation, the device's emotion engine analyzes the user's facial expressions and reactions in real time and collects data on emotional changes.

[0367] Step 9:

[0368] Users input feedback on the advice and send it to the server via their device. The server stores the feedback and sentiment data in a database to help improve the advice generation process in the future.

[0369] Step 10:

[0370] The server terminates the user's session and performs the logout procedure as needed. The terminal refreshes its screen and displays the user the login screen or menu screen.

[0371] (Example 2)

[0372] 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".

[0373] In modern career support, there is a need to address the individual needs of students and provide more appropriate advice. However, conventional systems do not adequately customize advice to reflect students' emotional states, and a more flexible and individualized system is needed. In particular, there is a lack of career guidance that is attentive to the anxieties and hopes that students feel, so new technologies are needed to generate advice that takes emotions into account.

[0374] 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.

[0375] In this invention, the server includes an information processing means for providing career support based on student input information, a presentation means for presenting generated advice, and a means for analyzing the user's emotions and customizing the advice based on that data. This enables highly accurate career advice tailored to the student's personality and emotional state.

[0376] "Information processing means" refers to means that perform data processing based on input information from students and have the function of providing necessary career support.

[0377] "Presentation means" refers to means that have the function of providing advice generated by information processing means to the user through visual or auditory means.

[0378] A "means for collecting feedback" refers to a means that has the function of collecting the reactions and opinions that users have given to the advice they have received.

[0379] A "database" is an information management system that stores collected feedback and historical data, and allows for searching and updating as needed.

[0380] A "means for analyzing emotions" refers to a means that has the function of inferring the emotional state from the user's facial expressions, voice, and input patterns, and acquiring that data.

[0381] A "generative AI model" is an artificial intelligence model that analyzes patterns based on input data and generates information optimized for the user.

[0382] "Means of customization" refers to a means of adjusting and modifying the advice generated based on collected emotional data to suit the individual needs of the user.

[0383] This invention provides a system for efficiently supporting students' career development. The system mainly consists of three main components: a server, a terminal, and a user.

[0384] The server is equipped with information processing capabilities and performs data processing necessary for career support based on input information from students. Specifically, the server uses a generative AI model to analyze the input data and generate optimal career advice. The server also works in conjunction with a database to accumulate feedback and historical data, which will be used to generate more precise advice in the future.

[0385] The terminal is a device for users to interact with the system and is equipped with presentation and emotion analysis capabilities. The terminal presents advice sent from the server to the user through a visual interface. The emotion analysis capabilities installed in the terminal analyze the user's facial expressions and voice in real time and collect emotion data. This emotion data is sent to the server and used to customize the advice.

[0386] Users access the platform via their devices and log in by entering their authentication information. After logging in, users select services such as career counseling, mock interviews, and document review, and answer questions based on those services. The user's responses and behavioral patterns are collected as emotional data through sentiment analysis.

[0387] For example, if a user asks for advice because they are interested in international relations but are unsure of a suitable career path, relevant questions are presented, and emotional data is collected along with the answers. The server inputs this data into a generating AI model to produce advice that includes the latest industry trends and necessary skills. This advice is then presented on the user's device as the most appropriate response to their emotional state.

[0388] As an example of a prompt, you can input instructions to the AI ​​model in the form of, "Generate optimal career advice for a student interested in international relations, taking into account their emotional state."

[0389] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0390] Step 1:

[0391] The user accesses the platform using their device and enters their authentication information on the login screen. The device sends the entered user ID and password to the server. The server authenticates the user by comparing it with the database and, after confirming its legitimacy, starts the user session. If authentication is successful, the server outputs a login success status to the device.

[0392] Step 2:

[0393] Once a user successfully logs in, the server generates service options based on the user's profile information (e.g., career counseling, mock interviews, resume review) and sends them to the terminal. The terminal visually displays the generated options to the user. The user selects the desired service from the presented options and sends it to the terminal as input. The terminal then sends the selected service information back to the server, and the process proceeds to the next step as output.

[0394] Step 3:

[0395] Based on the user's selection, the server begins data processing to generate the appropriate set of questions. This set of questions may include items to analyze the user's emotions, if necessary. The server creates the set of questions from the input data and sends it to the terminal. The terminal then presents the generated set of questions to the user.

[0396] Step 4:

[0397] The user answers questions through the device. The device uses its built-in sentiment analysis engine to analyze the user's facial expressions, voice, and behavioral patterns during input in real time, and acquires sentiment data. The response data and sentiment data are sent to the server through the device. The server receives this data as output for the next processing step.

[0398] Step 5:

[0399] The server inputs the received response data and sentiment data into a generating AI model. This AI model analyzes the input data and generates optimal career advice for the user. As output, the AI ​​model generates customized advice that takes into account factors such as industry trends, required skills, and the user's emotional state. This is then sent to the terminal.

[0400] Step 6:

[0401] The device presents the user with customized advice sent from the server. Upon presentation, the device again uses its emotion analysis engine to analyze the user's real-time facial expressions and reactions, obtaining feedback data. This feedback data is sent to the server via the device and stored as output to help improve future analysis accuracy.

[0402] (Application Example 2)

[0403] 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."

[0404] Food delivery users often find it difficult to make the right choice due to the wide variety of options available. Furthermore, few services offer personalized recommendations based on the user's emotional state. Addressing these issues and providing an optimal food delivery experience tailored to individual needs is crucial.

[0405] 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.

[0406] In this invention, the server includes an information processing means for providing advisory support based on user input information, a display means for presenting recommendations generated by the information processing means, and a means for collecting the user's response to the displayed recommendations after the recommendations generated based on the emotional state detected by the emotion evaluation means have been presented. This enables personalized food delivery selection according to the user's emotional state.

[0407] A "user" is an individual who uses the system to receive food delivery or other services.

[0408] "Input information" refers to a collection of data about the choices and requests that users provide to the system.

[0409] "Advisory support" is a process of providing suggestions and advice to help users make better choices.

[0410] "Information processing means" refers to a technical device or program that performs computational processing to generate recommendations based on input information.

[0411] "Display means" refers to devices or methods for presenting generated recommendations to users visually or audibly.

[0412] "Emotional evaluation means" refers to a technical device or method for evaluating a user's emotional state, often using devices such as cameras or microphones.

[0413] "Means for collecting responses" refers to technical methods or devices for collecting and analyzing user responses to displayed recommendations.

[0414] A "memory device" is a data storage medium or system used to store reaction and historical data.

[0415] A description of the embodiment for carrying out the invention will be provided.

[0416] This system is designed to provide personalized advice to users based on their emotional state during food delivery. The system works as follows:

[0417] First, the terminal receives input information from the user. At this stage, the user enters their preferences and desired type of cuisine into the terminal. The terminal is equipped with a camera and microphone, and through these devices, it acquires the user's facial expressions and voice data. This data is analyzed in real time by an emotion evaluation system. This analysis uses an emotion analysis library built in Python and the Google Cloud Speech-to-Text API.

[0418] Next, the server receives input information and emotional data sent from the terminal. Within the server, information processing tools generate food delivery options suitable for the user. This selection is based on the user's emotional state and past history, determining the most appropriate recommended menu for the user.

[0419] Finally, the selected recommended menu is presented to the user on their device through a display mechanism. The server then collects user response data and records it in storage. This data is used for further personalization in future visits.

[0420] For example, if a user is complaining of fatigue, this system can recommend comforting foods, such as soothing soups or relaxing teas. An example of a prompt from the generative AI model used would be, "Suggest relaxing food items based on the user's emotional state."

[0421] In this way, the system can provide a more personalized food delivery experience that is attentive to the user's emotions.

[0422] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0423] Step 1:

[0424] The terminal receives user input information, including the user's preferred cuisine type and allergy information. The terminal then centralizes this information and converts it into a format for transmission to the server. This clarifies the user's preferences and requirements.

[0425] Step 2:

[0426] The device uses its camera and microphone to capture the user's facial expressions and voice data. This data is essential for analysis by emotion assessment tools. Image processing and speech recognition technologies are used for the analysis, and the results are output as numerical data to identify the user's emotional state. This data is temporarily stored on the device.

[0427] Step 3:

[0428] The server receives input information and emotional data transmitted from the terminal. This data is analyzed by information processing tools operating within the server. Specifically, a machine learning algorithm is implemented to combine the user's preference patterns and emotional states. The algorithm utilizes past usage history and emotional data to generate recommendations for the most suitable dishes. This result is output as a recommended menu list.

[0429] Step 4:

[0430] The server sends the generated recommended menu to the terminal. The terminal displays the recommended menu to the user using a display device. The user reviews this and uses it to decide on their order. At this time, the user can also view detailed information about the menu provided on the terminal (price, nutritional information, etc.).

[0431] Step 5:

[0432] After the user views the recommended menu, the device uses its camera and microphone again to record the user's reactions. This allows for sentiment analysis of the user's reactions to the presented recommendations. The analyzed data is sent via the device to a server and stored in its storage device.

[0433] Step 6:

[0434] The server analyzes stored user response data and updates its machine learning model to reflect this in future recommendations. This continuous analysis and data feedback loop allows the system to improve accuracy over time. As a result, future recommendations become more personalized, providing users with the best possible choices.

[0435] 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.

[0436] 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.

[0437] 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.

[0438] [Third Embodiment]

[0439] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0440] 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.

[0441] 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).

[0442] 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.

[0443] 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.

[0444] 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).

[0445] 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.

[0446] 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.

[0447] 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.

[0448] 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.

[0449] 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.

[0450] 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".

[0451] This invention is a system that appropriately provides students with the information they need when choosing their career path and offers career support based on their individual values. This system is designed so that the three roles of server, terminal, and user work in coordination.

[0452] First, users access the platform via their smartphone or PC and log in. During login, the server processes the user's authentication information and verifies it against the database. Once authentication is approved, users can select options such as career counseling, mock interviews, and resume review.

[0453] When a user selects a desired service, the device displays a corresponding set of questions. These questions are dynamically generated by the server and are designed to gather information about the user's interests, values, and past performance. Once the user answers the questions, the information is sent to the server, where artificial intelligence further analyzes this data.

[0454] The server's artificial intelligence evaluates diverse career paths based on the user's characteristics and generates advice including appropriate job types, industry trends, and necessary skills. The generated advice is presented to the user via a terminal, and the user can provide feedback on its content. This feedback is collected by the server and used to improve future decision-making and suggestions.

[0455] To give a concrete example, suppose a user asks for advice saying, "I'm interested in design, but I don't know how to build a career in it." The device displays relevant questions and focuses on the user's values ​​and skills. The server analyzes the answers and provides advice that includes design industry trends, necessary skills, and appropriate learning resources. Based on this information, the user can plan their career.

[0456] A key feature of this system is that the advice provided to each user is highly personalized, as it is generated by combining the latest industry information with the user's individual characteristics. Furthermore, it boasts an advice algorithm that constantly evolves through a feedback loop. This allows the system to provide powerful support for students to make career choices they won't regret.

[0457] The following describes the processing flow.

[0458] Step 1:

[0459] Users access the platform using their smartphones or PCs and display the login screen. They then enter their email address and password to log in.

[0460] Step 2:

[0461] The terminal sends the entered authentication information to the server. The server compares the received authentication information with the database to verify that the user is legitimate. If authentication is successful, the server generates a session ID and sends an authentication success response to the terminal.

[0462] Step 3:

[0463] The terminal receives a successful authentication response from the server and displays a menu screen to the user that includes options such as career counseling, mock interviews, and document review. The user selects the service they wish to use.

[0464] Step 4:

[0465] The terminal sends the user's selection to the server. Based on the user's selection, the server dynamically generates an appropriate set of questions and sends them to the terminal.

[0466] Step 5:

[0467] The terminal displays a set of questions received from the server to the user and prompts the user to input information about their hobbies, values, and academic performance. The user then enters the necessary information based on the presented questions.

[0468] Step 6:

[0469] The terminal sends the user's input information to the server. The server passes the received data to artificial intelligence and begins the analysis process.

[0470] Step 7:

[0471] The server's artificial intelligence analyzes user data and generates career advice, including appropriate job roles, skills, and trends, based on the user's characteristics and industry trends. This advice is personalized according to the user's characteristics.

[0472] Step 8:

[0473] The server sends the generated carrier advice to the device. The device displays the received advice to the user. The user has the option to review the advice and provide feedback.

[0474] Step 9:

[0475] Users input feedback on the advice and send it to the server via their device. The server stores the received feedback in a database and uses it to improve future suggestion algorithms.

[0476] Step 10:

[0477] The server terminates the user's session and performs the logout procedure as needed. The terminal refreshes its screen and displays the user the login screen or menu screen.

[0478] (Example 1)

[0479] 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."

[0480] Many students face the challenge of finding a suitable career path based on their hobbies and values. Furthermore, career choices need to be based on the latest information, taking into account rapidly changing industry trends, but efficiently providing this information and offering personalized advice is difficult.

[0481] 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.

[0482] In this invention, the server includes means for verifying the user's authentication information, means for generating and presenting a set of questions corresponding to the service selected by the user, and means for using a generative AI model to analyze the user's response information and propose an appropriate career path. This makes it possible to provide personalized career advice based on the individual characteristics of the user.

[0483] "Authentication information" refers to the identification information necessary for a user to access the system, and includes things like usernames and passwords.

[0484] "Services" refer to options that users can select through the system, such as career counseling, mock interviews, and resume / document review.

[0485] A "question set" is a series of questions provided by the server to analyze user characteristics, designed to collect data on hobbies, values, and academic performance.

[0486] A "generative AI model" is an artificial intelligence technology used to analyze user response data and propose career paths based on individual characteristics.

[0487] A "career path" refers to the career or industry a user aspires to work in, and includes the necessary skills and experience to achieve it.

[0488] "Feedback" refers to the act of a user sending their opinions and evaluations of the information and advice provided to the server, which is used to improve the system and adjust the advice.

[0489] "Information storage means" refers to technologies such as databases for storing user feedback and historical data.

[0490] The embodiments for carrying out the present invention will be described in detail. The invention provides personalized career support to students and other users using an information processing system. The system overview and specific operation will be described below.

[0491] First, users access the system through devices such as PCs or smartphones. Users enter their authentication information on the login screen, and the server verifies this information against a database to perform authentication. Next, if authentication is successful, the user can access the service menu.

[0492] The service menu allows users to select options such as career counseling, mock interviews, and resume review. Depending on the selected service, the server dynamically generates a specific set of questions and sends them to the user's device. These questions are intended to gather information about the user's hobbies, values, past academic performance, and other relevant details.

[0493] When a user answers a question, the device sends this data to a server. The server uses a generative AI model to analyze the collected data and evaluate the optimal career path for the user. The AI ​​model operates based on prompts such as, "Please suggest the steps necessary for the user to pursue a design career." Based on the analysis, the server generates detailed advice including industry trends, required skills, and learning resources.

[0494] The generated advice is then presented to the user again via the terminal. The user can provide feedback on the content, and this feedback is stored on the server. The server can then use this feedback to improve future advice generation. For example, if a user asks, "I'm thinking of entering the medical industry, which qualifications would be advantageous?", the server will use an AI model to suggest specific methods for obtaining qualifications and relevant skills.

[0495] In this way, the system of the present invention can continue to provide users with personalized career support that reflects the latest information.

[0496] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0497] Step 1:

[0498] The user accesses the system using a terminal and enters authentication information on the login screen. The entered authentication information is sent from the terminal to the server. The server compares this information with data stored in the database to determine its authenticity. If authentication is successful, an approval message is returned to the terminal, and the user can proceed to the next step.

[0499] Step 2:

[0500] The server generates a service menu for approved users and sends it to their terminal. The user selects their desired service from options such as career counseling, mock interviews, and document review via their terminal. The user's selection information is then sent back to the server. The server receives this information and prepares for the next processing step.

[0501] Step 3:

[0502] The server dynamically generates a specific set of questions based on the service selected by the user. The generated set of questions is sent to the terminal and presented to the user. The generation of the question set takes into account the user's past history and certain industry trends.

[0503] Step 4:

[0504] The user answers questions displayed on the device and submits their answers. The device sends this answer data to the server. The server inputs the received data into a generating AI model and performs data analysis. The results of the analysis are used to generate advice later.

[0505] Step 5:

[0506] The server uses a generative AI model to analyze user response data. Specifically, it analyzes the user's hobbies, value system, and industry needs using prompt sentences, and then evaluates the optimal career path based on this. This analysis generates information on the necessary skills and learning resources.

[0507] Step 6:

[0508] The server sends the generated carrier information and advice to the terminal and presents it to the user. The user reviews this advice and provides feedback as needed. After feedback is submitted, that information is sent from the terminal to the server.

[0509] Step 7:

[0510] The server stores user feedback in its data storage system. This feedback is used as data to help generate advice and improve the system in the future. By analyzing the feedback and incorporating it into improvements to the generated AI model, the server can provide more accurate advice.

[0511] (Application Example 1)

[0512] 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."

[0513] Traditional career support systems have faced challenges in providing direct and immediate feedback and consultation to individual students, resulting in insufficient personalized information delivery. Furthermore, there is a lack of career advice based on real-world experience, and support for students in envisioning concrete future career paths is inadequate.

[0514] 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.

[0515] In this invention, the server includes an information processing means for providing career support based on student input information, a presentation means for presenting advice generated by the information processing means, and a means for directly interacting with the student in the real world while presenting the advice via a glasses-type device. This makes it possible to provide students with immediate, personalized career advice.

[0516] "Student input information" refers to data obtained from students regarding their personal interests, values, experiences, and academic performance related to their career paths and paths.

[0517] "Career support" refers to activities that provide students with the information, advice, and guidance they need when making future career choices.

[0518] "Information processing means" refers to a device or software that generates analysis and appropriate advice based on collected input information from students.

[0519] "Presentation means" refers to a device or interface for displaying or notifying students of the generated advice.

[0520] "Means of collecting feedback" refers to a device or function for obtaining students' opinions and evaluations of the advice they receive.

[0521] "Data storage means" refers to a database or storage device for storing collected feedback and student history data.

[0522] "A means of direct interaction in the real world while providing advice via a glasses-type device" refers to a method of meeting with students face-to-face using a glasses-type wearable device and providing career advice in real time.

[0523] "Industry trend information" refers to data and knowledge about the latest trends and changes in a specific industry.

[0524] "Required technical information" refers to information about the skills and technologies required for a particular occupation or industry.

[0525] "Interests and value systems" refer to the objects of interest and the set of standards and beliefs that each student considers important in life.

[0526] In this invention, the system involves a server, terminals, and users each fulfilling their respective roles and functioning in coordination. The server processes student input information and generates appropriate career support advice. The terminals, such as smartphones and personal computers, serve as the medium for presenting the generated advice. Furthermore, by utilizing glasses-type devices, direct interaction with the user in the real world is possible, enabling immediate feedback.

[0527] Specifically, a person wears a glasses-type device (e.g., smart glasses) and displays questions to students face-to-face, allowing them to input their answers in real time. The server collects the received answers in real time through a device such as Google Glass and analyzes them using an AI model (e.g., a generative AI model using TensorFlow). Based on the analysis, the server generates advice on the most suitable career path for the student, which is then visually presented to the user through the glasses-type device.

[0528] As a concrete example of this system, consider a scenario where a high school student meets with a specialist wearing glasses and asks, "I want to become an engineer, what kind of preparation do I need?" Based on the information gathered in this situation, the server generates and presents engineer-oriented advice, including appropriate university courses, necessary skill sets, and the latest industry trends.

[0529] An example of a prompt to input into the generating AI model is, "Please tell me how to provide appropriate career advice to a high school student aspiring to be an engineer, based on the user's interests and skills." This allows for highly personalized career support to be provided to the user, along with concrete, actionable steps.

[0530] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0531] Step 1:

[0532] The user wears a glasses-type device and logs into the terminal for carrier consultation.

[0533] In this process, the user enters personal information and interests, and this information is sent from the device to the server.

[0534] Based on the input information, the server uses an AI model to analyze data related to the user's interests and past performance.

[0535] The analysis output is a set of questions based on the user's interests and value system.

[0536] Step 2:

[0537] The server sends the generated set of questions to the glasses-type device via the terminal and displays them to the user.

[0538] The user answers questions through smart glasses.

[0539] User responses are entered into the terminal in real time and sent back to the server.

[0540] The server uses the input data to perform analysis using an AI model and calculates the data to determine the appropriate career path for the user.

[0541] Step 3:

[0542] The server presents advice generated by the AI ​​model to the user through a glasses-type device.

[0543] This advice is personalized and includes industry trend information and necessary technical information.

[0544] After the information is presented, users can ask additional questions or provide feedback.

[0545] Feedback is sent to the server via the device and used to improve future advice.

[0546] Step 4:

[0547] The server stores the collected feedback and user history in a data storage device.

[0548] This helps improve the accuracy of future advice and enhances our services.

[0549] The saved data will be used during new user sessions, contributing to an improved user experience.

[0550] 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.

[0551] This invention is a system that provides career support based on student input information, and in particular, incorporates an emotion engine to provide advice that takes the user's emotions into consideration. This system consists of three main components: a server, a terminal, and a user.

[0552] First, the user accesses the platform using their device and logs in. The user enters their authentication information, which the server then uses to verify the user's legitimacy by comparing it against the database. Once logged in, the device presents the user with options such as career counseling, mock interviews, and resume review.

[0553] When a user selects a desired service, the device notifies the server. The server generates a set of questions based on the user's selections, which may include questions for sentiment analysis. The set of questions is presented to the user via the device, and the user answers them. At this time, the device has an emotion engine built in to measure the user's emotional state, analyzing facial expressions, voice, and behavioral patterns during input to infer the user's emotions.

[0554] The server receives user response data and sentiment data collected from the terminal and has artificial intelligence analyze this data. Based on the response data and sentiment data, the AI ​​generates career advice that is best suited to the user's personality. This advice is customized not only with industry trend information and required skills information, but also with content that is best suited to the user's emotional state.

[0555] The generated advice is sent to the terminal via the server and presented to the user. When presenting the advice, the terminal analyzes the user's facial expressions and reactions using an emotion engine, collecting real-time feedback based on emotional changes. This allows the server to accumulate data that further optimizes the advice generation process.

[0556] As a concrete example, suppose a user asks for advice because they are interested in international relations but are unsure of a suitable career path. The device presents the user with a series of related questions, and in the process, transmits emotional data recognized by the emotion engine. Based on this, the server customizes and presents advice that incorporates the latest trends in international relations, specific skills, and elements that are likely to motivate the user.

[0557] By using an emotional engine in conjunction with traditional career advice, it becomes possible to provide support that is more attentive to the user and tailored to their individual condition and emotions.

[0558] The following describes the processing flow.

[0559] Step 1:

[0560] Users access the platform using their smartphones or PCs and are directed to the login screen. They then enter their email address and password to log in.

[0561] Step 2:

[0562] The terminal sends the entered authentication information to the server. The server compares the received authentication information with the database to verify that the user is legitimate. If authentication is successful, the server generates a session ID and sends an authentication success response to the terminal.

[0563] Step 3:

[0564] The terminal receives a successful authentication response from the server and displays a menu screen to the user that includes options such as career counseling, mock interviews, and document review. The user selects the service they wish to use.

[0565] Step 4:

[0566] The terminal sends the user's selection to the server. Based on the user's selection, the server dynamically generates an appropriate set of questions and sends them to the terminal. This set of questions also includes questions for sentiment analysis.

[0567] Step 5:

[0568] The terminal displays a set of questions received from the server to the user, prompting them to provide input about their hobbies, values, academic performance, and emotions. While the user answers the questions for emotion analysis, the emotion engine built into the terminal senses the user's facial expressions and voice, and collects emotion data.

[0569] Step 6:

[0570] The device sends the user's response data and sentiment data to the server. The server passes the received data to artificial intelligence and begins the analysis process.

[0571] Step 7:

[0572] The server's artificial intelligence analyzes user response data and sentiment data to generate career advice that takes into account user characteristics, industry trends, and factors that tend to motivate the user. This advice is customized and highly personalized based on the sentiment data.

[0573] Step 8:

[0574] The server sends the generated career advice to the device. The device displays the received advice to the user. During presentation, the device's emotion engine analyzes the user's facial expressions and reactions in real time and collects data on emotional changes.

[0575] Step 9:

[0576] Users input feedback on the advice and send it to the server via their device. The server stores the feedback and sentiment data in a database to help improve the advice generation process in the future.

[0577] Step 10:

[0578] The server terminates the user's session and performs the logout procedure as needed. The terminal refreshes its screen and displays the user the login screen or menu screen.

[0579] (Example 2)

[0580] 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."

[0581] In modern career support, there is a need to address the individual needs of students and provide more appropriate advice. However, conventional systems do not adequately customize advice to reflect students' emotional states, and a more flexible and individualized system is needed. In particular, there is a lack of career guidance that is attentive to the anxieties and hopes that students feel, so new technologies are needed to generate advice that takes emotions into account.

[0582] 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.

[0583] In this invention, the server includes an information processing means for providing career support based on student input information, a presentation means for presenting generated advice, and a means for analyzing the user's emotions and customizing the advice based on that data. This enables highly accurate career advice tailored to the student's personality and emotional state.

[0584] "Information processing means" refers to means that perform data processing based on input information from students and have the function of providing necessary career support.

[0585] "Presentation means" refers to means that have the function of providing advice generated by information processing means to the user through visual or auditory means.

[0586] A "means for collecting feedback" refers to a means that has the function of collecting the reactions and opinions that users have given to the advice they have received.

[0587] A "database" is an information management system that stores collected feedback and historical data, and allows for searching and updating as needed.

[0588] A "means for analyzing emotions" refers to a means that has the function of inferring the emotional state from the user's facial expressions, voice, and input patterns, and acquiring that data.

[0589] A "generative AI model" is an artificial intelligence model that analyzes patterns based on input data and generates information optimized for the user.

[0590] "Means of customization" refers to a means of adjusting and modifying the advice generated based on collected emotional data to suit the individual needs of the user.

[0591] This invention provides a system for efficiently supporting students' career development. The system mainly consists of three main components: a server, a terminal, and a user.

[0592] The server is equipped with information processing capabilities and performs data processing necessary for career support based on input information from students. Specifically, the server uses a generative AI model to analyze the input data and generate optimal career advice. The server also works in conjunction with a database to accumulate feedback and historical data, which will be used to generate more precise advice in the future.

[0593] The terminal is a device for users to interact with the system and is equipped with presentation and emotion analysis capabilities. The terminal presents advice sent from the server to the user through a visual interface. The emotion analysis capabilities installed in the terminal analyze the user's facial expressions and voice in real time and collect emotion data. This emotion data is sent to the server and used to customize the advice.

[0594] Users access the platform via their devices and log in by entering their authentication information. After logging in, users select services such as career counseling, mock interviews, and document review, and answer questions based on those services. The user's responses and behavioral patterns are collected as emotional data through sentiment analysis.

[0595] For example, if a user asks for advice because they are interested in international relations but are unsure of a suitable career path, relevant questions are presented, and emotional data is collected along with the answers. The server inputs this data into a generating AI model to produce advice that includes the latest industry trends and necessary skills. This advice is then presented on the user's device as the most appropriate response to their emotional state.

[0596] As an example of a prompt, you can input instructions to the AI ​​model in the form of, "Generate optimal career advice for a student interested in international relations, taking into account their emotional state."

[0597] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0598] Step 1:

[0599] The user accesses the platform using their device and enters their authentication information on the login screen. The device sends the entered user ID and password to the server. The server authenticates the user by comparing it with the database and, after confirming its legitimacy, starts the user session. If authentication is successful, the server outputs a login success status to the device.

[0600] Step 2:

[0601] Once a user successfully logs in, the server generates service options based on the user's profile information (e.g., career counseling, mock interviews, resume review) and sends them to the terminal. The terminal visually displays the generated options to the user. The user selects the desired service from the presented options and sends it to the terminal as input. The terminal then sends the selected service information back to the server, and the process proceeds to the next step as output.

[0602] Step 3:

[0603] Based on the user's selection, the server begins data processing to generate the appropriate set of questions. This set of questions may include items to analyze the user's emotions, if necessary. The server creates the set of questions from the input data and sends it to the terminal. The terminal then presents the generated set of questions to the user.

[0604] Step 4:

[0605] The user answers questions through the device. The device uses its built-in sentiment analysis engine to analyze the user's facial expressions, voice, and behavioral patterns during input in real time, and acquires sentiment data. The response data and sentiment data are sent to the server through the device. The server receives this data as output for the next processing step.

[0606] Step 5:

[0607] The server inputs the received response data and sentiment data into a generating AI model. This AI model analyzes the input data and generates optimal career advice for the user. As output, the AI ​​model generates customized advice that takes into account factors such as industry trends, required skills, and the user's emotional state. This is then sent to the terminal.

[0608] Step 6:

[0609] The device presents the user with customized advice sent from the server. Upon presentation, the device again uses its emotion analysis engine to analyze the user's real-time facial expressions and reactions, obtaining feedback data. This feedback data is sent to the server via the device and stored as output to help improve future analysis accuracy.

[0610] (Application Example 2)

[0611] 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."

[0612] Food delivery users often find it difficult to make the right choice due to the wide variety of options available. Furthermore, few services offer personalized recommendations based on the user's emotional state. Addressing these issues and providing an optimal food delivery experience tailored to individual needs is crucial.

[0613] 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.

[0614] In this invention, the server includes an information processing means for providing advisory support based on user input information, a display means for presenting recommendations generated by the information processing means, and a means for collecting the user's response to the displayed recommendations after the recommendations generated based on the emotional state detected by the emotion evaluation means have been presented. This enables personalized food delivery selection according to the user's emotional state.

[0615] A "user" is an individual who uses the system to receive food delivery or other services.

[0616] "Input information" refers to a collection of data about the choices and requests that users provide to the system.

[0617] "Advisory support" is a process of providing suggestions and advice to help users make better choices.

[0618] "Information processing means" refers to a technical device or program that performs computational processing to generate recommendations based on input information.

[0619] "Display means" refers to devices or methods for presenting generated recommendations to users visually or audibly.

[0620] "Emotional evaluation means" refers to a technical device or method for evaluating a user's emotional state, often using devices such as cameras or microphones.

[0621] "Means for collecting responses" refers to technical methods or devices for collecting and analyzing user responses to displayed recommendations.

[0622] A "memory device" is a data storage medium or system used to store reaction and historical data.

[0623] A description of the embodiment for carrying out the invention will be provided.

[0624] This system is designed to provide personalized advice to users based on their emotional state during food delivery. The system works as follows:

[0625] First, the terminal receives input information from the user. At this stage, the user enters their preferences and desired type of cuisine into the terminal. The terminal is equipped with a camera and microphone, and through these devices, it acquires the user's facial expressions and voice data. This data is analyzed in real time by an emotion evaluation system. This analysis uses an emotion analysis library built in Python and the Google Cloud Speech-to-Text API.

[0626] Next, the server receives input information and emotional data sent from the terminal. Within the server, information processing tools generate food delivery options suitable for the user. This selection is based on the user's emotional state and past history, determining the most appropriate recommended menu for the user.

[0627] Finally, the selected recommended menu is presented to the user on their device through a display mechanism. The server then collects user response data and records it in storage. This data is used for further personalization in future visits.

[0628] For example, if a user is complaining of fatigue, this system can recommend comforting foods, such as soothing soups or relaxing teas. An example of a prompt from the generative AI model used would be, "Suggest relaxing food items based on the user's emotional state."

[0629] In this way, the system can provide a more personalized food delivery experience that is attentive to the user's emotions.

[0630] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0631] Step 1:

[0632] The terminal receives user input information, including the user's preferred cuisine type and allergy information. The terminal then centralizes this information and converts it into a format for transmission to the server. This clarifies the user's preferences and requirements.

[0633] Step 2:

[0634] The device uses its camera and microphone to capture the user's facial expressions and voice data. This data is essential for analysis by emotion assessment tools. Image processing and speech recognition technologies are used for the analysis, and the results are output as numerical data to identify the user's emotional state. This data is temporarily stored on the device.

[0635] Step 3:

[0636] The server receives input information and emotional data transmitted from the terminal. This data is analyzed by information processing tools operating within the server. Specifically, a machine learning algorithm is implemented to combine the user's preference patterns and emotional states. The algorithm utilizes past usage history and emotional data to generate recommendations for the most suitable dishes. This result is output as a recommended menu list.

[0637] Step 4:

[0638] The server sends the generated recommended menu to the terminal. The terminal displays the recommended menu to the user using a display device. The user reviews this and uses it to decide on their order. At this time, the user can also view detailed information about the menu provided on the terminal (price, nutritional information, etc.).

[0639] Step 5:

[0640] After the user views the recommended menu, the device uses its camera and microphone again to record the user's reactions. This allows for sentiment analysis of the user's reactions to the presented recommendations. The analyzed data is sent via the device to a server and stored in its storage device.

[0641] Step 6:

[0642] The server analyzes stored user response data and updates its machine learning model to reflect this in future recommendations. This continuous analysis and data feedback loop allows the system to improve accuracy over time. As a result, future recommendations become more personalized, providing users with the best possible choices.

[0643] 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.

[0644] 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.

[0645] 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.

[0646] [Fourth Embodiment]

[0647] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0648] 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.

[0649] 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).

[0650] 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.

[0651] 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.

[0652] 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).

[0653] 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.

[0654] 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.

[0655] 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.

[0656] 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.

[0657] 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.

[0658] 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.

[0659] 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".

[0660] This invention is a system that appropriately provides students with the information they need when choosing their career path and offers career support based on their individual values. This system is designed so that the three roles of server, terminal, and user work in coordination.

[0661] First, users access the platform via their smartphone or PC and log in. During login, the server processes the user's authentication information and verifies it against the database. Once authentication is approved, users can select options such as career counseling, mock interviews, and resume review.

[0662] When a user selects a desired service, the device displays a corresponding set of questions. These questions are dynamically generated by the server and are designed to gather information about the user's interests, values, and past performance. Once the user answers the questions, the information is sent to the server, where artificial intelligence further analyzes this data.

[0663] The server's artificial intelligence evaluates diverse career paths based on the user's characteristics and generates advice including appropriate job types, industry trends, and necessary skills. The generated advice is presented to the user via a terminal, and the user can provide feedback on its content. This feedback is collected by the server and used to improve future decision-making and suggestions.

[0664] To give a concrete example, suppose a user asks for advice saying, "I'm interested in design, but I don't know how to build a career in it." The device displays relevant questions and focuses on the user's values ​​and skills. The server analyzes the answers and provides advice that includes design industry trends, necessary skills, and appropriate learning resources. Based on this information, the user can plan their career.

[0665] A key feature of this system is that the advice provided to each user is highly personalized, as it is generated by combining the latest industry information with the user's individual characteristics. Furthermore, it boasts an advice algorithm that constantly evolves through a feedback loop. This allows the system to provide powerful support for students to make career choices they won't regret.

[0666] The following describes the processing flow.

[0667] Step 1:

[0668] Users access the platform using their smartphones or PCs and display the login screen. They then enter their email address and password to log in.

[0669] Step 2:

[0670] The terminal sends the entered authentication information to the server. The server compares the received authentication information with the database to verify that the user is legitimate. If authentication is successful, the server generates a session ID and sends an authentication success response to the terminal.

[0671] Step 3:

[0672] The terminal receives a successful authentication response from the server and displays a menu screen to the user that includes options such as career counseling, mock interviews, and document review. The user selects the service they wish to use.

[0673] Step 4:

[0674] The terminal sends the user's selection to the server. Based on the user's selection, the server dynamically generates an appropriate set of questions and sends them to the terminal.

[0675] Step 5:

[0676] The terminal displays a set of questions received from the server to the user and prompts the user to input information about their hobbies, values, and academic performance. The user then enters the necessary information based on the presented questions.

[0677] Step 6:

[0678] The terminal sends the user's input information to the server. The server passes the received data to artificial intelligence and begins the analysis process.

[0679] Step 7:

[0680] The server's artificial intelligence analyzes user data and generates career advice, including appropriate job roles, skills, and trends, based on the user's characteristics and industry trends. This advice is personalized according to the user's characteristics.

[0681] Step 8:

[0682] The server sends the generated carrier advice to the device. The device displays the received advice to the user. The user has the option to review the advice and provide feedback.

[0683] Step 9:

[0684] Users input feedback on the advice and send it to the server via their device. The server stores the received feedback in a database and uses it to improve future suggestion algorithms.

[0685] Step 10:

[0686] The server terminates the user's session and performs the logout procedure as needed. The terminal refreshes its screen and displays the user the login screen or menu screen.

[0687] (Example 1)

[0688] 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".

[0689] Many students face the challenge of finding a suitable career path based on their hobbies and values. Furthermore, career choices need to be based on the latest information, taking into account rapidly changing industry trends, but efficiently providing this information and offering personalized advice is difficult.

[0690] 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.

[0691] In this invention, the server includes means for verifying the user's authentication information, means for generating and presenting a set of questions corresponding to the service selected by the user, and means for using a generative AI model to analyze the user's response information and propose an appropriate career path. This makes it possible to provide personalized career advice based on the individual characteristics of the user.

[0692] "Authentication information" refers to the identification information necessary for a user to access the system, and includes things like usernames and passwords.

[0693] "Services" refer to options that users can select through the system, such as career counseling, mock interviews, and resume / document review.

[0694] A "question set" is a series of questions provided by the server to analyze user characteristics, designed to collect data on hobbies, values, and academic performance.

[0695] A "generative AI model" is an artificial intelligence technology used to analyze user response data and propose career paths based on individual characteristics.

[0696] A "career path" refers to the career or industry a user aspires to work in, and includes the necessary skills and experience to achieve it.

[0697] "Feedback" refers to the act of a user sending their opinions and evaluations of the information and advice provided to the server, which is used to improve the system and adjust the advice.

[0698] "Information storage means" refers to technologies such as databases for storing user feedback and historical data.

[0699] The embodiments for carrying out the present invention will be described in detail. The invention provides personalized career support to students and other users using an information processing system. The system overview and specific operation will be described below.

[0700] First, users access the system through devices such as PCs or smartphones. Users enter their authentication information on the login screen, and the server verifies this information against a database to perform authentication. Next, if authentication is successful, the user can access the service menu.

[0701] The service menu allows users to select options such as career counseling, mock interviews, and resume review. Depending on the selected service, the server dynamically generates a specific set of questions and sends them to the user's device. These questions are intended to gather information about the user's hobbies, values, past academic performance, and other relevant details.

[0702] When a user answers a question, the device sends this data to a server. The server uses a generative AI model to analyze the collected data and evaluate the optimal career path for the user. The AI ​​model operates based on prompts such as, "Please suggest the steps necessary for the user to pursue a design career." Based on the analysis, the server generates detailed advice including industry trends, required skills, and learning resources.

[0703] The generated advice is then presented to the user again via the terminal. The user can provide feedback on the content, and this feedback is stored on the server. The server can then use this feedback to improve future advice generation. For example, if a user asks, "I'm thinking of entering the medical industry, which qualifications would be advantageous?", the server will use an AI model to suggest specific methods for obtaining qualifications and relevant skills.

[0704] In this way, the system of the present invention can continue to provide users with personalized career support that reflects the latest information.

[0705] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0706] Step 1:

[0707] The user accesses the system using a terminal and enters authentication information on the login screen. The entered authentication information is sent from the terminal to the server. The server compares this information with data stored in the database to determine its authenticity. If authentication is successful, an approval message is returned to the terminal, and the user can proceed to the next step.

[0708] Step 2:

[0709] The server generates a service menu for approved users and sends it to their terminal. The user selects their desired service from options such as career counseling, mock interviews, and document review via their terminal. The user's selection information is then sent back to the server. The server receives this information and prepares for the next processing step.

[0710] Step 3:

[0711] The server dynamically generates a specific set of questions based on the service selected by the user. The generated set of questions is sent to the terminal and presented to the user. The generation of the question set takes into account the user's past history and certain industry trends.

[0712] Step 4:

[0713] The user answers questions displayed on the device and submits their answers. The device sends this answer data to the server. The server inputs the received data into a generating AI model and performs data analysis. The results of the analysis are used to generate advice later.

[0714] Step 5:

[0715] The server uses a generative AI model to analyze user response data. Specifically, it analyzes the user's hobbies, value system, and industry needs using prompt sentences, and then evaluates the optimal career path based on this. This analysis generates information on the necessary skills and learning resources.

[0716] Step 6:

[0717] The server sends the generated carrier information and advice to the terminal and presents it to the user. The user reviews this advice and provides feedback as needed. After feedback is submitted, that information is sent from the terminal to the server.

[0718] Step 7:

[0719] The server stores user feedback in its data storage system. This feedback is used as data to help generate advice and improve the system in the future. By analyzing the feedback and incorporating it into improvements to the generated AI model, the server can provide more accurate advice.

[0720] (Application Example 1)

[0721] 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".

[0722] Traditional career support systems have faced challenges in providing direct and immediate feedback and consultation to individual students, resulting in insufficient personalized information delivery. Furthermore, there is a lack of career advice based on real-world experience, and support for students in envisioning concrete future career paths is inadequate.

[0723] 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.

[0724] In this invention, the server includes an information processing means for providing career support based on student input information, a presentation means for presenting advice generated by the information processing means, and a means for directly interacting with the student in the real world while presenting the advice via a glasses-type device. This makes it possible to provide students with immediate, personalized career advice.

[0725] "Student input information" refers to data obtained from students regarding their personal interests, values, experiences, and academic performance related to their career paths and paths.

[0726] "Career support" refers to activities that provide students with the information, advice, and guidance they need when making future career choices.

[0727] "Information processing means" refers to a device or software that generates analysis and appropriate advice based on collected input information from students.

[0728] "Presentation means" refers to a device or interface for displaying or notifying students of the generated advice.

[0729] "Means of collecting feedback" refers to a device or function for obtaining students' opinions and evaluations of the advice they receive.

[0730] "Data storage means" refers to a database or storage device for storing collected feedback and student history data.

[0731] "A means of direct interaction in the real world while providing advice via a glasses-type device" refers to a method of meeting with students face-to-face using a glasses-type wearable device and providing career advice in real time.

[0732] "Industry trend information" refers to data and knowledge about the latest trends and changes in a specific industry.

[0733] "Required technical information" refers to information about the skills and technologies required for a particular occupation or industry.

[0734] "Interests and value systems" refer to the objects of interest and the set of standards and beliefs that each student considers important in life.

[0735] In this invention, the system involves a server, terminals, and users each fulfilling their respective roles and functioning in coordination. The server processes student input information and generates appropriate career support advice. The terminals, such as smartphones and personal computers, serve as the medium for presenting the generated advice. Furthermore, by utilizing glasses-type devices, direct interaction with the user in the real world is possible, enabling immediate feedback.

[0736] Specifically, a person wears a glasses-type device (e.g., smart glasses) and displays questions to students face-to-face, allowing them to input their answers in real time. The server collects the received answers in real time through a device such as Google Glass and analyzes them using an AI model (e.g., a generative AI model using TensorFlow). Based on the analysis, the server generates advice on the most suitable career path for the student, which is then visually presented to the user through the glasses-type device.

[0737] As a concrete example of this system, consider a scenario where a high school student meets with a specialist wearing glasses and asks, "I want to become an engineer, what kind of preparation do I need?" Based on the information gathered in this situation, the server generates and presents engineer-oriented advice, including appropriate university courses, necessary skill sets, and the latest industry trends.

[0738] An example of a prompt to input into the generating AI model is, "Please tell me how to provide appropriate career advice to a high school student aspiring to be an engineer, based on the user's interests and skills." This allows for highly personalized career support to be provided to the user, along with concrete, actionable steps.

[0739] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0740] Step 1:

[0741] The user wears a glasses-type device and logs into the terminal for carrier consultation.

[0742] In this process, the user enters personal information and interests, and this information is sent from the device to the server.

[0743] Based on the input information, the server uses an AI model to analyze data related to the user's interests and past performance.

[0744] The analysis output is a set of questions based on the user's interests and value system.

[0745] Step 2:

[0746] The server sends the generated set of questions to the glasses-type device via the terminal and displays them to the user.

[0747] The user answers questions through smart glasses.

[0748] User responses are entered into the terminal in real time and sent back to the server.

[0749] The server uses the input data to perform analysis using an AI model and calculates the data to determine the appropriate career path for the user.

[0750] Step 3:

[0751] The server presents advice generated by the AI ​​model to the user through a glasses-type device.

[0752] This advice is personalized and includes industry trend information and necessary technical information.

[0753] After the information is presented, users can ask additional questions or provide feedback.

[0754] Feedback is sent to the server via the device and used to improve future advice.

[0755] Step 4:

[0756] The server stores the collected feedback and user history in a data storage device.

[0757] This helps improve the accuracy of future advice and enhances our services.

[0758] The saved data will be used during new user sessions, contributing to an improved user experience.

[0759] 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.

[0760] This invention is a system that provides career support based on student input information, and in particular, incorporates an emotion engine to provide advice that takes the user's emotions into consideration. This system consists of three main components: a server, a terminal, and a user.

[0761] First, the user accesses the platform using their device and logs in. The user enters their authentication information, which the server then uses to verify the user's legitimacy by comparing it against the database. Once logged in, the device presents the user with options such as career counseling, mock interviews, and resume review.

[0762] When a user selects a desired service, the device notifies the server. The server generates a set of questions based on the user's selections, which may include questions for sentiment analysis. The set of questions is presented to the user via the device, and the user answers them. At this time, the device has an emotion engine built in to measure the user's emotional state, analyzing facial expressions, voice, and behavioral patterns during input to infer the user's emotions.

[0763] The server receives user response data and sentiment data collected from the terminal and has artificial intelligence analyze this data. Based on the response data and sentiment data, the AI ​​generates career advice that is best suited to the user's personality. This advice is customized not only with industry trend information and required skills information, but also with content that is best suited to the user's emotional state.

[0764] The generated advice is sent to the terminal via the server and presented to the user. When presenting the advice, the terminal analyzes the user's facial expressions and reactions using an emotion engine, collecting real-time feedback based on emotional changes. This allows the server to accumulate data that further optimizes the advice generation process.

[0765] As a concrete example, suppose a user asks for advice because they are interested in international relations but are unsure of a suitable career path. The device presents the user with a series of related questions, and in the process, transmits emotional data recognized by the emotion engine. Based on this, the server customizes and presents advice that incorporates the latest trends in international relations, specific skills, and elements that are likely to motivate the user.

[0766] By using an emotional engine in conjunction with traditional career advice, it becomes possible to provide support that is more attentive to the user and tailored to their individual condition and emotions.

[0767] The following describes the processing flow.

[0768] Step 1:

[0769] Users access the platform using their smartphones or PCs and are directed to the login screen. They then enter their email address and password to log in.

[0770] Step 2:

[0771] The terminal sends the entered authentication information to the server. The server compares the received authentication information with the database to verify that the user is legitimate. If authentication is successful, the server generates a session ID and sends an authentication success response to the terminal.

[0772] Step 3:

[0773] The terminal receives a successful authentication response from the server and displays a menu screen to the user that includes options such as career counseling, mock interviews, and document review. The user selects the service they wish to use.

[0774] Step 4:

[0775] The terminal sends the user's selection to the server. Based on the user's selection, the server dynamically generates an appropriate set of questions and sends them to the terminal. This set of questions also includes questions for sentiment analysis.

[0776] Step 5:

[0777] The terminal displays a set of questions received from the server to the user, prompting them to provide input about their hobbies, values, academic performance, and emotions. While the user answers the questions for emotion analysis, the emotion engine built into the terminal senses the user's facial expressions and voice, and collects emotion data.

[0778] Step 6:

[0779] The device sends the user's response data and sentiment data to the server. The server passes the received data to artificial intelligence and begins the analysis process.

[0780] Step 7:

[0781] The server's artificial intelligence analyzes user response data and sentiment data to generate career advice that takes into account user characteristics, industry trends, and factors that tend to motivate the user. This advice is customized and highly personalized based on the sentiment data.

[0782] Step 8:

[0783] The server sends the generated career advice to the device. The device displays the received advice to the user. During presentation, the device's emotion engine analyzes the user's facial expressions and reactions in real time and collects data on emotional changes.

[0784] Step 9:

[0785] Users input feedback on the advice and send it to the server via their device. The server stores the feedback and sentiment data in a database to help improve the advice generation process in the future.

[0786] Step 10:

[0787] The server terminates the user's session and performs the logout procedure as needed. The terminal refreshes its screen and displays the user the login screen or menu screen.

[0788] (Example 2)

[0789] 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".

[0790] In modern career support, there is a need to address the individual needs of students and provide more appropriate advice. However, conventional systems do not adequately customize advice to reflect students' emotional states, and a more flexible and individualized system is needed. In particular, there is a lack of career guidance that is attentive to the anxieties and hopes that students feel, so new technologies are needed to generate advice that takes emotions into account.

[0791] 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.

[0792] In this invention, the server includes an information processing means for providing career support based on student input information, a presentation means for presenting generated advice, and a means for analyzing the user's emotions and customizing the advice based on that data. This enables highly accurate career advice tailored to the student's personality and emotional state.

[0793] "Information processing means" refers to means that perform data processing based on input information from students and have the function of providing necessary career support.

[0794] "Presentation means" refers to means that have the function of providing advice generated by information processing means to the user through visual or auditory means.

[0795] A "means for collecting feedback" refers to a means that has the function of collecting the reactions and opinions that users have given to the advice they have received.

[0796] A "database" is an information management system that stores collected feedback and historical data, and allows for searching and updating as needed.

[0797] A "means for analyzing emotions" refers to a means that has the function of inferring the emotional state from the user's facial expressions, voice, and input patterns, and acquiring that data.

[0798] A "generative AI model" is an artificial intelligence model that analyzes patterns based on input data and generates information optimized for the user.

[0799] "Means of customization" refers to a means of adjusting and modifying the advice generated based on collected emotional data to suit the individual needs of the user.

[0800] This invention provides a system for efficiently supporting students' career development. The system mainly consists of three main components: a server, a terminal, and a user.

[0801] The server is equipped with information processing capabilities and performs data processing necessary for career support based on input information from students. Specifically, the server uses a generative AI model to analyze the input data and generate optimal career advice. The server also works in conjunction with a database to accumulate feedback and historical data, which will be used to generate more precise advice in the future.

[0802] The terminal is a device for users to interact with the system and is equipped with presentation and emotion analysis capabilities. The terminal presents advice sent from the server to the user through a visual interface. The emotion analysis capabilities installed in the terminal analyze the user's facial expressions and voice in real time and collect emotion data. This emotion data is sent to the server and used to customize the advice.

[0803] Users access the platform via their devices and log in by entering their authentication information. After logging in, users select services such as career counseling, mock interviews, and document review, and answer questions based on those services. The user's responses and behavioral patterns are collected as emotional data through sentiment analysis.

[0804] For example, if a user asks for advice because they are interested in international relations but are unsure of a suitable career path, relevant questions are presented, and emotional data is collected along with the answers. The server inputs this data into a generating AI model to produce advice that includes the latest industry trends and necessary skills. This advice is then presented on the user's device as the most appropriate response to their emotional state.

[0805] As an example of a prompt, you can input instructions to the AI ​​model in the form of, "Generate optimal career advice for a student interested in international relations, taking into account their emotional state."

[0806] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0807] Step 1:

[0808] The user accesses the platform using their device and enters their authentication information on the login screen. The device sends the entered user ID and password to the server. The server authenticates the user by comparing it with the database and, after confirming its legitimacy, starts the user session. If authentication is successful, the server outputs a login success status to the device.

[0809] Step 2:

[0810] Once a user successfully logs in, the server generates service options based on the user's profile information (e.g., career counseling, mock interviews, resume review) and sends them to the terminal. The terminal visually displays the generated options to the user. The user selects the desired service from the presented options and sends it to the terminal as input. The terminal then sends the selected service information back to the server, and the process proceeds to the next step as output.

[0811] Step 3:

[0812] Based on the user's selection, the server begins data processing to generate the appropriate set of questions. This set of questions may include items to analyze the user's emotions, if necessary. The server creates the set of questions from the input data and sends it to the terminal. The terminal then presents the generated set of questions to the user.

[0813] Step 4:

[0814] The user answers questions through the device. The device uses its built-in sentiment analysis engine to analyze the user's facial expressions, voice, and behavioral patterns during input in real time, and acquires sentiment data. The response data and sentiment data are sent to the server through the device. The server receives this data as output for the next processing step.

[0815] Step 5:

[0816] The server inputs the received response data and sentiment data into a generating AI model. This AI model analyzes the input data and generates optimal career advice for the user. As output, the AI ​​model generates customized advice that takes into account factors such as industry trends, required skills, and the user's emotional state. This is then sent to the terminal.

[0817] Step 6:

[0818] The device presents the user with customized advice sent from the server. Upon presentation, the device again uses its emotion analysis engine to analyze the user's real-time facial expressions and reactions, obtaining feedback data. This feedback data is sent to the server via the device and stored as output to help improve future analysis accuracy.

[0819] (Application Example 2)

[0820] 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".

[0821] Food delivery users often find it difficult to make the right choice due to the wide variety of options available. Furthermore, few services offer personalized recommendations based on the user's emotional state. Addressing these issues and providing an optimal food delivery experience tailored to individual needs is crucial.

[0822] 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.

[0823] In this invention, the server includes an information processing means for providing advisory support based on user input information, a display means for presenting recommendations generated by the information processing means, and a means for collecting the user's response to the displayed recommendations after the recommendations generated based on the emotional state detected by the emotion evaluation means have been presented. This enables personalized food delivery selection according to the user's emotional state.

[0824] A "user" is an individual who uses the system to receive food delivery or other services.

[0825] "Input information" refers to a collection of data about the choices and requests that users provide to the system.

[0826] "Advisory support" is a process of providing suggestions and advice to help users make better choices.

[0827] "Information processing means" refers to a technical device or program that performs computational processing to generate recommendations based on input information.

[0828] "Display means" refers to devices or methods for presenting generated recommendations to users visually or audibly.

[0829] "Emotional evaluation means" refers to a technical device or method for evaluating a user's emotional state, often using devices such as cameras or microphones.

[0830] "Means for collecting responses" refers to technical methods or devices for collecting and analyzing user responses to displayed recommendations.

[0831] A "memory device" is a data storage medium or system used to store reaction and historical data.

[0832] A description of the embodiment for carrying out the invention will be provided.

[0833] This system is designed to provide personalized advice to users based on their emotional state during food delivery. The system works as follows:

[0834] First, the terminal receives input information from the user. At this stage, the user enters their preferences and desired type of cuisine into the terminal. The terminal is equipped with a camera and microphone, and through these devices, it acquires the user's facial expressions and voice data. This data is analyzed in real time by an emotion evaluation system. This analysis uses an emotion analysis library built in Python and the Google Cloud Speech-to-Text API.

[0835] Next, the server receives input information and emotional data sent from the terminal. Within the server, information processing tools generate food delivery options suitable for the user. This selection is based on the user's emotional state and past history, determining the most appropriate recommended menu for the user.

[0836] Finally, the selected recommended menu is presented to the user on their device through a display mechanism. The server then collects user response data and records it in storage. This data is used for further personalization in future visits.

[0837] For example, if a user is complaining of fatigue, this system can recommend comforting foods, such as soothing soups or relaxing teas. An example of a prompt from the generative AI model used would be, "Suggest relaxing food items based on the user's emotional state."

[0838] In this way, the system can provide a more personalized food delivery experience that is attentive to the user's emotions.

[0839] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0840] Step 1:

[0841] The terminal receives user input information, including the user's preferred cuisine type and allergy information. The terminal then centralizes this information and converts it into a format for transmission to the server. This clarifies the user's preferences and requirements.

[0842] Step 2:

[0843] The device uses its camera and microphone to capture the user's facial expressions and voice data. This data is essential for analysis by emotion assessment tools. Image processing and speech recognition technologies are used for the analysis, and the results are output as numerical data to identify the user's emotional state. This data is temporarily stored on the device.

[0844] Step 3:

[0845] The server receives input information and emotional data transmitted from the terminal. This data is analyzed by information processing tools operating within the server. Specifically, a machine learning algorithm is implemented to combine the user's preference patterns and emotional states. The algorithm utilizes past usage history and emotional data to generate recommendations for the most suitable dishes. This result is output as a recommended menu list.

[0846] Step 4:

[0847] The server sends the generated recommended menu to the terminal. The terminal displays the recommended menu to the user using a display device. The user reviews this and uses it to decide on their order. At this time, the user can also view detailed information about the menu provided on the terminal (price, nutritional information, etc.).

[0848] Step 5:

[0849] After the user views the recommended menu, the device uses its camera and microphone again to record the user's reactions. This allows for sentiment analysis of the user's reactions to the presented recommendations. The analyzed data is sent via the device to a server and stored in its storage device.

[0850] Step 6:

[0851] The server analyzes stored user response data and updates its machine learning model to reflect this in future recommendations. This continuous analysis and data feedback loop allows the system to improve accuracy over time. As a result, future recommendations become more personalized, providing users with the best possible choices.

[0852] 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.

[0853] 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.

[0854] 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 robot 414.

[0855] 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.

[0856] 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.

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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."

[0861] 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.

[0862] 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.

[0863] 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.

[0864] 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.

[0865] 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.

[0866] 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.

[0867] 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.

[0868] 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.

[0869] 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.

[0870] 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.

[0871] 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.

[0872] 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 as being incorporated by reference.

[0873] The following is further disclosed regarding the embodiments described above.

[0874] (Claim 1)

[0875] An information processing system that provides career support based on student input information,

[0876] A presentation means that presents advice generated by the information processing means,

[0877] A means of collecting feedback on the advice given,

[0878] A database for storing the aforementioned feedback and historical data,

[0879] A system that includes this.

[0880] (Claim 2)

[0881] The system according to claim 1, characterized in that the generated advice includes industry trend information and required skills information.

[0882] (Claim 3)

[0883] The system according to claim 1, characterized by having artificial intelligence to analyze students' hobbies and value systems and identify the optimal career path.

[0884] "Example 1"

[0885] (Claim 1)

[0886] A means of verifying user authentication information,

[0887] A means of generating and presenting a set of questions corresponding to the service selected by the user,

[0888] A means of using a generative AI model to analyze user response information and propose an appropriate career path,

[0889] A means of presenting proposed career information to the user,

[0890] A means of collecting and storing user feedback,

[0891] Information storage means for storing the aforementioned feedback and historical data,

[0892] A system that includes this.

[0893] (Claim 2)

[0894] The system according to claim 1, characterized in that the generated career information includes industry trend information and required skills information.

[0895] (Claim 3)

[0896] The system according to claim 1, characterized by having artificial intelligence that analyzes the user's hobbies, value system, and past performance, and uses prompt sentences to identify an appropriate career path.

[0897] "Application Example 1"

[0898] (Claim 1)

[0899] An information processing system that provides career support based on student input information,

[0900] A presentation means that presents advice generated by the information processing means,

[0901] A means of collecting feedback on the advice given,

[0902] A data storage means for storing the aforementioned feedback and historical data,

[0903] A means of direct interaction in the real world while providing advice through a glasses-type device,

[0904] A system that includes this.

[0905] (Claim 2)

[0906] The system according to claim 1, characterized in that the generated advice includes industry trend information and necessary technical information.

[0907] (Claim 3)

[0908] The system according to claim 1, characterized by having artificial intelligence to analyze students' interests and value systems and identify the optimal career path.

[0909] "Example 2 of combining an emotion engine"

[0910] (Claim 1)

[0911] An information processing system that provides career support based on student input information,

[0912] A presentation means that presents advice generated by the information processing means,

[0913] A means of collecting feedback on the advice given,

[0914] A database for storing the aforementioned feedback and historical data,

[0915] Having means to analyze the user's emotions, and means to customize advice based on said analysis,

[0916] A means of collecting real-time user feedback and improving the accuracy of the analysis,

[0917] A system that includes this.

[0918] (Claim 2)

[0919] The system according to claim 1, characterized in that the generated advice includes industry trend information and required skills information, and is customized according to the user's emotional state.

[0920] (Claim 3)

[0921] The system according to claim 1, characterized by having artificial intelligence to analyze students' hobbies and value systems to identify the optimal career path, and further providing empathetic advice to users using sentiment analysis.

[0922] "Application example 2 when combining with an emotional engine"

[0923] (Claim 1)

[0924] An information processing system that provides advisory support based on user input information,

[0925] A display means that presents recommendations generated by the aforementioned information processing means,

[0926] A means for collecting user responses to the displayed recommendations after the recommendation has been presented based on the emotional state detected by the emotion evaluation means,

[0927] A memory device for storing the aforementioned reaction and historical data,

[0928] A system that includes this.

[0929] (Claim 2)

[0930] The system according to claim 1, characterized in that the generated recommendations include activity trend information and necessary technical information.

[0931] (Claim 3)

[0932] The system according to claim 1, characterized by having machine learning to analyze the user's unique characteristics and preference system and identify an optimized course of action. [Explanation of Symbols]

[0933] 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. An information processing system that provides career support based on student input information, A presentation means that presents advice generated by the information processing means, A means of collecting feedback on the advice given, A database for storing the aforementioned feedback and historical data, A system that includes this.

2. The system according to claim 1, characterized in that the generated advice includes industry trend information and required skills information.

3. The system according to claim 1, characterized by having artificial intelligence to analyze students' hobbies and value systems and identify the optimal career path.

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