system

Abstract

We provide the system. [Solution] A means for analyzing data on user characteristics, interests, experiences, and skills acquired from an information processing device, Methods for analyzing industrial market data imported from external databases, A means for generating suitable occupations and career paths for users based on the aforementioned analysis and results, A means of presenting generated occupations and career paths to users, A means of acquiring information in conjunction with home automation devices and enabling interaction with users, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] The modern labor market is diversified, and it is difficult for individuals to find a suitable occupation or career path. In particular, extracting useful data from a vast amount of information and finding a suitable job is a major challenge. Also, the support in overall career formation, such as acquiring necessary skills and matching job offers, is not sufficient. Conventional systems have not been able to provide comprehensive and real-time support for these problems.

Means for Solving the Problems

[0005] This invention provides a system that generates the optimal occupation and career path for a user by analyzing data related to the user's personality, interests, experience, and skills using an information processing device and an external database. It also has the function of identifying the necessary skills according to the user's set occupational goals, proposing specific learning plans and resources, and tracking and evaluating the user's learning progress. Furthermore, it provides job postings that match the user's criteria through job search and matching functions, and supports the process leading up to application. This realizes personalized career support for each individual user, supporting effective career development.

[0006] An "information processing device" is a system that includes hardware and software for collecting, processing, and analyzing information.

[0007] "Users" refer to individuals who use this system to receive support for their career development and skill improvement.

[0008] "Personality" refers to a set of consistent characteristics that manifest in an individual's thoughts, feelings, and actions.

[0009] "Interest" refers to the concern or curiosity an individual has towards a particular activity or field.

[0010] "Experience" refers to the totality of knowledge and skills an individual has acquired through past activities and work.

[0011] "Skills" refer to the practical knowledge and techniques necessary to accomplish a specific job or activity.

[0012] A "database" refers to a collection of information that is systematically stored and easily retrieved as needed.

[0013] "Labor market data" refers to data that includes statistics and trends related to employment in a specific region or industry.

[0014] "Career path" refers to the path and growth plan that an individual progresses in their career, including work experience, education, etc.

[0015] "Learning plan" refers to the staged learning design constructed to acquire specific skills and knowledge.

[0016] "Job information" refers to the information on employment opportunities provided by companies or organizations, including job content, conditions, work location, etc.

Brief Description of Drawings

[0017] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] [ It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. W [Figure 12]It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Modes for Carrying Out the Invention

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

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

[0020] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include 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.

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

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

[0023] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0025] [First Embodiment]

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

[0027] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0030] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0034] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

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

[0038] This invention provides an information processing system that enables users to effectively develop their careers. This system includes functions that comprehensively support self-analysis, aptitude testing, skill development support, and job matching. Specific embodiments are described below.

[0039] The server first receives information about the user's personality, interests, experience, and skills entered through their terminal. Based on this, the analysis engine on the server automatically analyzes the data and calculates suitable occupations and career paths for the user. This process utilizes machine learning algorithms and is optimized by considering similar past profiles and current market trends. The analysis results are displayed on the terminal, and the user can receive feedback.

[0040] Furthermore, the server identifies the necessary skills based on the user's set career goals and generates a learning plan that aligns with market trends. In this process, it incorporates external educational resources and online course information to present the user with the most suitable learning path. By receiving this, users can gradually improve their skills. Their progress is tracked through their device, contributing to increased motivation.

[0041] Regarding job matching, the server periodically collects the latest information from external job databases and matches users based on their desired conditions and skill sets. This result is displayed on the user's device as a list of job postings, showing the job description, conditions, and application link. This allows users to quickly access suitable jobs and proceed with the application process.

[0042] For example, if a user wishes to switch careers to a marketing position and enters their current experience and required skills via their device, the server will analyze the information, recommend online courses suitable for a marketing major, and present a trial career path. At the same time, it will filter and provide currently available marketing-related job postings. In this way, users can receive consistent support at every stage of their career development and quickly obtain the information and means to achieve their goals.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] Users use their devices to input information about their personality, interests, experiences, and skills into a self-assessment questionnaire.

[0046] Step 2:

[0047] The terminal sends the entered information to the server.

[0048] Step 3:

[0049] The server passes the user data it receives to the analysis engine, which then begins the analysis using natural language processing.

[0050] Step 4:

[0051] The server uses machine learning algorithms to compare the user's profile with similar historical data.

[0052] Step 5:

[0053] The server calculates suitable occupations and career paths for the user based on the analysis results and sends the results to the terminal.

[0054] Step 6:

[0055] The terminal receives data from the server and displays the analysis results on the user interface.

[0056] Step 7:

[0057] Users set career goals and input the skills they aim to acquire and the knowledge they want to learn into the device.

[0058] Step 8:

[0059] The terminal sends user input to the server.

[0060] Step 9:

[0061] The server references a market database to identify the necessary skills related to the career goals.

[0062] Step 10:

[0063] The system evaluates the gap between the server's required skills and the user's current skills, and generates a learning plan to bridge that gap.

[0064] Step 11:

[0065] The device displays the learning plan received from the server on the user's dashboard, providing a progress tracking function.

[0066] Step 12:

[0067] The user enters their desired job requirements into a terminal and sends them to the system.

[0068] Step 13:

[0069] The server collects job information from the job database in real time.

[0070] Step 14:

[0071] The server filters job postings based on the user's criteria and selects those with the highest degree of suitability.

[0072] Step 15:

[0073] The terminal displays a list of job postings retrieved from the server and presents the job description and application link to the user.

[0074] (Example 1)

[0075] 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."

[0076] In today's labor market, it is difficult for individual users to find the career path that best suits them. Furthermore, there is a lack of consistent support for skill development and efficient job searching. In this context, there is a need for a system that enables users to find suitable occupations, acquire necessary skills, and access job postings quickly.

[0077] 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.

[0078] In this invention, the server includes means for analyzing data on characteristics obtained from the user, means for analyzing external labor market information, and means for obtaining information from external educational resources to generate a learning plan. This allows the user to receive suggestions for the optimal career path, improve necessary skills, and make quick decisions based on the latest job information.

[0079] "User" refers to an individual who uses this system to explore and manage their occupation and career path.

[0080] "Data related to characteristics" refers to information related to the user's personality, interests, work experience, and skills.

[0081] "Means of analysis" refers to methods and processes for using collected data to identify suitable occupations and paths for users.

[0082] "External labor market information" refers to information obtained from external databases regarding current market trends and employment opportunities.

[0083] "Means of analysis" refers to methods for evaluating market information and guiding users to the most suitable occupations and career paths.

[0084] "Educational resources" refer to online courses and learning materials provided to users for skill improvement.

[0085] A "learning plan" refers to a plan that includes specific steps and schedules to support the acquisition of necessary skills in order to achieve the professional goals set by the user.

[0086] "Job postings" refer to information provided by various companies and organizations regarding job requirements, salaries, and job descriptions.

[0087] "Search methods" refer to the methods used to find suitable job postings from a database based on the user's desired conditions.

[0088] "Selection method" refers to the process of identifying the most suitable job postings from search results and presenting them to the user.

[0089] This invention is an information processing system that supports users in effectively forming their careers through terminals. The system mainly consists of a server and terminals, thereby providing users with flexible and efficient career management.

[0090] The user's first step is to input data about their personality, interests, experience, and skills via a device. The device then formats the input information appropriately and sends it to the server. The server uses an analysis engine equipped with AI technology and machine learning algorithms to analyze the received data. This calculates suitable occupations and career paths for the user. Specifically, data analysis software operating on a cloud platform or industry-standard DBMS can be used.

[0091] Furthermore, the server retrieves the latest labor market information from external databases and integrates it with the analysis results to generate a learning plan. Based on this information, the server suggests optimal educational resources tailored to the user's career goals and supports skill improvement. These educational resources include online learning platforms and industry-specific online courses.

[0092] Regarding the provision of job information, the server periodically scans external job databases and filters job postings based on the user's skill set and desired conditions. The selected job postings are displayed as a list on the user's terminal, enabling quick application.

[0093] For example, if a user enters "I'm thinking of changing jobs to pursue a marketing position," the server analyzes that information, considers relevant skills and experience, and recommends marketing-specific career paths and educational resources. Furthermore, by providing a list of the latest job postings in the marketing field, users can quickly access and apply for suitable positions.

[0094] An example of a prompt message would be, "I am considering a career change to pursue a marketing position. Given my current skill set and experience, what career paths are possible for me, and what should I study?" This collaborative operation across the entire system allows users to effectively manage their careers and navigate the path to their desired profession.

[0095] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0096] Step 1:

[0097] Users input basic data about their personality, interests, experiences, and skills using their own devices. This data is converted into a structured format such as JSON and prepared to be sent to the server. During this preparation stage, the device checks the integrity of the data and verifies that the entered information is valid.

[0098] Step 2:

[0099] The server analyzes the data received from the terminal. AI technology and machine learning algorithms are used for the analysis. User data, as input, is compared with a database of similar historical profiles and market trends to derive suitable occupations and career paths. As output, appropriate career paths are provided, and this information is sent to the user's terminal.

[0100] Step 3:

[0101] The server retrieves labor market information from an external database and integrates it with the analysis results. This external market information includes industry trends and job postings. In this step, the server considers the market data as input, makes appropriate adjustments to the user's career plan, and generates a learning plan. The learning plan is sent to the user's terminal, presenting a roadmap for specific skill development.

[0102] Step 4:

[0103] The server collects information from external educational resources and builds a learning plan tailored to the user's career goals. This step includes a process of extracting information on appropriate online courses and learning materials based on the entered user data. The learning plan clearly outlines the steps necessary for the user's skill improvement, and progress can be monitored on the device.

[0104] Step 5:

[0105] The system searches for and matches job postings. The server scans external job databases and filters job postings to match the user's specified preferences and skill set. Based on the user's preferences, the system selects the most suitable jobs, and these postings are displayed as a list on the user's terminal. This list includes application links, allowing the user to apply directly.

[0106] Step 6:

[0107] Users utilize information provided by their devices to advance their career development. Based on suggested career paths and learning plans, they acquire skills aligned with their goals and apply for jobs. This step supports the entire process from the user's learning to the evaluation of their progress.

[0108] Each processing step involves the server, terminal, and user working together to create a system that comprehensively supports users in designing their career paths.

[0109] (Application Example 1)

[0110] 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."

[0111] Currently, it is a challenging task for individual users to effectively acquire information about career development and improve their skills in daily life. In particular, finding the optimal occupation and career path based on one's own characteristics and creating and executing a learning plan accordingly requires a great deal of manual work. Furthermore, searching for job postings and obtaining application information must be done individually, which is time-consuming and laborious. Therefore, there is a need for consistent support and automated services to solve these problems.

[0112] 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.

[0113] In this invention, the server includes means for analyzing data on the user's characteristics, interests, experience, and skills acquired from an information processing device, means for analyzing industrial market data imported from an external database, and means for acquiring information in cooperation with home automation equipment and enabling interaction with the user. As a result, the user not only automatically receives individually optimized occupations and career plans, but also receives continuous feedback and progress management through interaction via home automation equipment.

[0114] An "information processing device" is an electronic device that has the ability to receive, process, and transmit digital data, and is used to manage information related to the user.

[0115] "Characteristics" refer to attributes related to a user's personality and behavior, and are the basic information that forms the basis of their individual profile.

[0116] "Interests" refer to the fields and themes that users are particularly interested in and passionate about, and are factors that determine the direction of their career development.

[0117] "Experience" refers to the achievements and knowledge gained through past work and activities, and is an important factor that influences future career choices.

[0118] "Skills" refer to the knowledge and abilities required to perform specific tasks or duties, and are indicators used to measure professional competence.

[0119] "Industrial market data" refers to aggregated external information related to economic activity, such as industry trends and employment conditions, and is used for career recommendations through analysis.

[0120] "Home automation devices" refer to digital devices used for information sharing and automated tasks within the home environment, enabling interaction with the user.

[0121] "Analysis means" refers to technical methods for analyzing data about users using information processing equipment to evaluate vocational aptitude and abilities.

[0122] "Analysis means" refers to the processing steps involved in handling data acquired from external sources and generating information that is useful to the user.

[0123] "Dialogue methods" refer to technologies that enable communication between users and systems, and are necessary to provide continuous support.

[0124] The system for carrying out this invention is constructed using an information processing device, a home automation device, and an external database. The server first acquires data on the user's characteristics, interests, experience, and skills through the information processing device. This data is processed by an analysis engine on the server, which generates the most suitable occupation and career path for the user.

[0125] Furthermore, the server retrieves industry market data from an external database and supplements the analysis results. Based on this information, it identifies the skills the user needs and proposes an optimal learning plan and external educational resources. The home automation device presents the user with acquired information and feedback in real time through interaction. This enables the user to efficiently improve their skills in their daily life.

[0126] Home automation devices also search for employment opportunities based on the user's preferences and provide matching job postings. Users can use this information to quickly proceed with the application process. A specific example of use is a user considering a career change taking a career aptitude test and acquiring new skills through recommended learning courses.

[0127] An example of a prompt using a generative AI model is, "What is the best career path and necessary skills to leverage your current experience and move into a new field?" Based on this prompt, the system provides a specific career development plan tailored to the user.

[0128] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0129] Step 1:

[0130] The server receives data from the information processing device regarding the user's characteristics, interests, experience, and skills. This data includes the user's past work history, educational background, and personality test results. Using this as initial input data, the analysis engine begins processing.

[0131] Step 2:

[0132] The server analyzes the received user data using machine learning algorithms. During the data analysis process, clustering and classification techniques are used to generate user profiles based on their characteristics. This results in the output of suitable occupational categories and career paths for each user.

[0133] Step 3:

[0134] The server retrieves industry market data from an external database. This data includes the latest market trends, in-demand skills, and salary information. The server integrates this data with analysis results to generate job and career information optimized for the user.

[0135] Step 4:

[0136] The server presents this generated occupation and career information through home automation devices. The information presented includes learning plans based on the skill sets the user desires and market popularity. The home automation devices interact with the user and accumulate feedback.

[0137] Step 5:

[0138] Based on the information presented, the user sets their own career goals. The server identifies the necessary skills based on these new goals and suggests external educational resources (e.g., online courses and learning materials). This resource information is presented to the user and incorporated into their learning plan.

[0139] Step 6:

[0140] Based on the user's specified preferences, the server searches an external database for job postings and lists suitable employment opportunities. These listed job postings are then provided to the user via a home automation device, along with an application interface.

[0141] Step 7:

[0142] The server and home automation devices work together to collect user feedback and apply that feedback to improve future career development and job search services. This will enable more personalized information and support for users.

[0143] 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.

[0144] This invention combines an emotion engine with an information processing system that supports users' career development, thereby enabling personalized support that takes into account the user's emotions. This system uses an information processing device to analyze data on the user's personality, interests, experience, and skills, and further analyzes labor market data obtained from an external database to suggest suitable occupations and career paths for the user.

[0145] The server receives text or voice data entered by the user on the device and sends it to the emotion engine. This emotion engine uses natural language processing technology to analyze the user's emotions in real time. For example, if the emotion engine determines that the user is stressed or unmotivated, the system takes this into account and adjusts the career plan, providing advice that includes more encouragement and support.

[0146] Furthermore, the analysis results of this emotion engine are also considered when proposing learning plans. The server analyzes the user's emotional state and adjusts learning resources and progress schedules based on that analysis, thereby reducing the user's burden and supporting efficient and effective skill development. In this way, the system is able to understand the user's overall psychological state and propose a flexible learning plan based on that understanding.

[0147] For example, when a user begins a learning plan to pursue a marketing career, the system uses an emotion engine to initially confirm that the user is highly motivated. The server then sets positive learning goals and tracks progress in detail. However, if a decline in motivation is detected along the way, the server adjusts the learning goals based on the emotion engine's assessment and proposes a revised plan at a less stressful pace for the user. It can also provide messages to boost the user's motivation and offer encouraging topics related to skill acquisition.

[0148] This system allows users to develop a personalized career and improve their skills while reducing emotional burden.

[0149] The following describes the processing flow.

[0150] Step 1:

[0151] Users input information about their personality, interests, experiences, and skills using their devices. They can also input their mood and feelings for the day via voice or text as needed.

[0152] Step 2:

[0153] The terminal sends the entered data and voice / text information to the server.

[0154] Step 3:

[0155] The server passes the user's data to the analysis engine, and the analysis begins. Information about personality, interests, experience, and skills is analyzed based on their respective profiles.

[0156] Step 4:

[0157] The server uses an emotion engine to analyze the user's emotional state from received audio or text data. Natural language processing is employed, and emotional indicators are identified as numerical values ​​or categories.

[0158] Step 5:

[0159] The server generates the optimal occupation and career path for the user based on the analysis results. Occupational suggestions are provided using an approach tailored to the user's emotional state.

[0160] Step 6:

[0161] The server takes into account the emotional state determined by the emotion engine and adjusts the tone of messages and suggestions to the user as needed.

[0162] Step 7:

[0163] The device receives carrier suggestions and messages from the server and displays them to the user.

[0164] Step 8:

[0165] The user inputs their career goals and desired skill set from their device and sends it to the server.

[0166] Step 9:

[0167] The server identifies the skills required by the user based on their career goals. This process includes a gap analysis between the current skill level and market needs.

[0168] Step 10:

[0169] The server takes into account the analysis results from the emotion engine and customizes and proposes a learning plan in a way that reduces the user's psychological burden.

[0170] Step 11:

[0171] The device displays the generated learning plan to the user and provides a function to continuously track their progress.

[0172] Step 12:

[0173] The server periodically updates job data and filters job postings in real time to match the user's desired conditions.

[0174] Step 13:

[0175] The terminal displays job postings received from the server to the user and provides a link to apply.

[0176] In this way, the system comprehensively supports career development while taking into account the user's emotional state.

[0177] (Example 2)

[0178] 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".

[0179] In today's professional environment, there is a demand for prompt and appropriate suggestions of occupations and career paths tailored to individual clients. However, traditional methods often fail to consider the emotional state of each client, resulting in proposed career plans that are not always suitable for their psychological condition. This can lead to decreased motivation and insufficient results in skill development and career choices.

[0180] 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.

[0181] In this invention, the server includes means for interpreting information about the user's characteristics, interests, experiences, and abilities; means for analyzing employment market information collected from external sources; and means for analyzing the user's emotional state using an emotion engine and adjusting career paths based on that analysis. This enables the suggestion of personalized, emotion-responsive occupational and career plans to the user.

[0182] An "information processing system" is a device that collects and processes user characteristics and external information to perform data analysis and make suggestions.

[0183] "Information sources" refer to external databases or data feeds that provide data on the employment market.

[0184] "Characteristics" refer to the individual features that make up a user's personality and behavioral patterns.

[0185] "Interest" refers to the things that users are interested in or concerned with.

[0186] "Experience" is the accumulation of things that a user has learned and experienced in the past.

[0187] "Ability" refers to the technical or specialized skills and knowledge that the user possesses.

[0188] The "emotion engine" is a program based on natural language processing technology that analyzes user input data and evaluates their emotional state.

[0189] A "career path" refers to a plan that outlines the occupations a user can pursue and the direction of their career development.

[0190] "Personalized advice" refers to advice provided based on the user's unique circumstances and feelings.

[0191] To implement this invention, an information processing system equipped with an emotion engine is required. The server first receives text or voice data from the user via a terminal. This data includes the user's characteristics, interests, experiences, abilities, and current emotional state. Next, the server passes the received data to the emotion engine, which analyzes the user's emotional state in real time. This analysis utilizes natural language processing technology, such as using libraries like Google's Natural Language API.

[0192] The server analyzes the latest employment market information obtained from external sources based on the analysis results. This analysis utilizes commonly used big data processing platforms such as Apache® Hadoop. This generates suitable occupations and career paths for the user and provides advice. During this process, a career plan generated using a generative AI model is presented to the user.

[0193] For example, if a user enters "I'm interested in digital marketing" into their device, the server sends this information to the emotion engine and data analysis engine to develop an optimal career plan. If high stress levels are detected in the user, the server provides a flexible learning plan to alleviate that pressure. An example of a prompt would be, "Please create a learning plan for a marketing career. Include content that reduces user stress and increases motivation."

[0194] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0195] Step 1:

[0196] Users input text or voice data about their occupation and career through their device. This input data includes the user's characteristics, interests, experience, and abilities. The device then transmits this data to the server.

[0197] Step 2:

[0198] The server sends the received data to the emotion engine. The emotion engine uses natural language processing technology to analyze the user's input data in real time and evaluate their emotional state. Specifically, it determines the user's stress level and motivation based on emotional indicators extracted from the text. It generates data indicating the emotional state as output.

[0199] Step 3:

[0200] The server analyzes the analyzed emotional state data and the user's characteristics, interests, experiences, and abilities, along with the latest job market information obtained from external sources. Specifically, it uses big data processing tools to identify the most suitable occupations and career paths for the user. This analysis generates a list of candidate occupations and career paths to suggest to the user.

[0201] Step 4:

[0202] The server creates a career plan optimized for the user based on the generated list of candidate career paths and the user's emotional state. A generative AI model is used to generate a customized plan tailored to the user's needs and emotional state. The output includes a career plan with specific job suggestions and a learning plan.

[0203] Step 5:

[0204] The server sends the final generated career plan to the terminal and presents it to the user. Based on the information presented, the user can decide on future career choices and actions for skill development. If feedback or further suggestions are needed, the system takes this into account and adjusts the plan accordingly.

[0205] (Application Example 2)

[0206] 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 device 14 will be referred to as the "terminal."

[0207] Traditional career development support systems provided job suggestions based on users' personality and skill data, but they failed to consider changes in users' emotions and motivation, resulting in insufficient personalized support. Furthermore, they were unable to dynamically adjust learning plans based on users' daily emotions, making efficient skill improvement difficult.

[0208] 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.

[0209] In this invention, the server includes means for analyzing data on the user's personality, interests, experiences, and skills acquired from an information processing device; means for analyzing labor market data imported from an external database; and means for analyzing the user's emotional state in real time using an emotion analysis engine and making adjustments to the generated occupation and career path based on the emotional information. This enables the provision of personalized career plans tailored to each user's emotional state and the dynamic adjustment of effective learning plans.

[0210] An "information processing device" is a system for acquiring and analyzing data related to a user's personality, interests, experiences, and skills.

[0211] An "external database" is a data storage system that accumulates information about the labor market and allows this information to be imported for analysis.

[0212] An "emotion analysis engine" is an analysis system equipped with technology that determines the emotional state of a user in real time based on text and voice data acquired from them.

[0213] A "career path" is a plan that outlines suitable occupations for the user and the career development process leading up to them.

[0214] A "learning plan" is a plan that includes a procedure and resource allocation aimed at acquiring the skills necessary to achieve the occupational goals set by the user.

[0215] "Adjustment" refers to the process of dynamically modifying plans and proposals based on the user's current emotional state and progress.

[0216] "Job postings" refer to data on employment opportunities obtained from the labor market, including details of jobs that users can apply for.

[0217] The system for implementing this invention aims to provide users with career development support optimized for their needs. This system functions as an information processing device, an external database, and an emotion analysis engine.

[0218] The server retrieves data on the user's personality, interests, experience, and skills from an information processing device. By analyzing this data, it gains a detailed understanding of the user's characteristics. In addition, the server imports labor market data from an external database and analyzes it to generate suitable occupations and career paths for the user.

[0219] Furthermore, the emotion analysis engine processes the user's input text and voice data in real time to determine their emotional state. Specifically, it uses natural language processing technology to analyze text and capture changes in emotions and motivation. For example, it can utilize natural language processing libraries using Python (such as NLTK or spaCy).

[0220] Based on the results of emotion analysis, the server dynamically adjusts the career path and learning plan. This enables flexible support tailored to the user's emotional state and progress. Furthermore, hardware devices equipped with microphones and speakers can be used, allowing for voice data input and interaction.

[0221] As a concrete example, if a user reports work-related stress on a given day, the system recognizes that emotion through emotion analysis and proposes new relaxing activities in the learning plan. An example of a related generative AI model prompt is as follows:

[0222] "When a user is feeling stressed, what suggestions do you offer? Please include relaxation methods as well."

[0223] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0224] Step 1:

[0225] The user inputs text or voice data into the device. The device receives this data and converts it into digital data. This data is then sent to the server as input.

[0226] Step 2:

[0227] The server processes the received digital data using an information processing device. Specifically, it utilizes natural language processing technology to analyze the user's personality, interests, experiences, and skills, and generates a personality profile. This profile is then output.

[0228] Step 3:

[0229] The server accesses an external database to retrieve current labor market data. This data includes various information about occupations. The information retrieved from the database is analyzed as input, and the results of the labor market trend analysis are output.

[0230] Step 4:

[0231] The server integrates the generated personality profile with analyzed labor market information. Based on this, it generates suitable occupations and career paths for the user. Personalized career suggestions are output using the generated AI model.

[0232] Step 5:

[0233] The received text or audio data is sent to the sentiment analysis engine. The sentiment analysis engine uses natural language processing to analyze the data and determine the user's real-time emotional state. The emotional information obtained during this process is then output.

[0234] Step 6:

[0235] The server dynamically adjusts the generated carrier path based on emotional information. By incorporating emotional support elements, it redesigns the carrier plan to better suit the user. This redesigned plan is then output.

[0236] Step 7:

[0237] The system presents users with redesigned career paths and learning plans via their devices. Furthermore, it offers suggestions for relaxation and motivation enhancement. In this process, it utilizes prompts from a generated AI model to ensure optimal communication.

[0238] 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.

[0239] 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.

[0240] 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.

[0241] [Second Embodiment]

[0242] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0243] 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.

[0244] 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).

[0245] 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.

[0246] 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.

[0247] 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).

[0248] 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.

[0249] 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.

[0250] 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.

[0251] 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.

[0252] 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.

[0253] 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".

[0254] This invention provides an information processing system that enables users to effectively develop their careers. This system includes functions that comprehensively support self-analysis, aptitude testing, skill development support, and job matching. Specific embodiments are described below.

[0255] The server first receives information about the user's personality, interests, experience, and skills entered through their terminal. Based on this, the analysis engine on the server automatically analyzes the data and calculates suitable occupations and career paths for the user. This process utilizes machine learning algorithms and is optimized by considering similar past profiles and current market trends. The analysis results are displayed on the terminal, and the user can receive feedback.

[0256] Furthermore, the server identifies the necessary skills based on the user's set career goals and generates a learning plan that aligns with market trends. In this process, it incorporates external educational resources and online course information to present the user with the most suitable learning path. By receiving this, users can gradually improve their skills. Their progress is tracked through their device, contributing to increased motivation.

[0257] Regarding job matching, the server periodically collects the latest information from external job databases and matches users based on their desired conditions and skill sets. This result is displayed on the user's device as a list of job postings, showing the job description, conditions, and application link. This allows users to quickly access suitable jobs and proceed with the application process.

[0258] For example, if a user wishes to switch careers to a marketing position and enters their current experience and required skills via their device, the server will analyze the information, recommend online courses suitable for a marketing major, and present a trial career path. At the same time, it will filter and provide currently available marketing-related job postings. In this way, users can receive consistent support at every stage of their career development and quickly obtain the information and means to achieve their goals.

[0259] The following describes the processing flow.

[0260] Step 1:

[0261] Users use their devices to input information about their personality, interests, experiences, and skills into a self-assessment questionnaire.

[0262] Step 2:

[0263] The terminal sends the entered information to the server.

[0264] Step 3:

[0265] The server passes the user data it receives to the analysis engine, which then begins the analysis using natural language processing.

[0266] Step 4:

[0267] The server uses machine learning algorithms to compare the user's profile with similar historical data.

[0268] Step 5:

[0269] The server calculates suitable occupations and career paths for the user based on the analysis results and sends the results to the terminal.

[0270] Step 6:

[0271] The terminal receives data from the server and displays the analysis results on the user interface.

[0272] Step 7:

[0273] Users set career goals and input the skills they aim to acquire and the knowledge they want to learn into the device.

[0274] Step 8:

[0275] The terminal sends user input to the server.

[0276] Step 9:

[0277] The server refers to the market database and identifies the necessary skills related to the career goal.

[0278] Step 10:

[0279] The server evaluates the difference between the required skills and the user's current skills and generates a learning plan to bridge the gap.

[0280] Step 11:

[0281] The terminal displays the learning plan received from the server on the user's dashboard and provides a progress tracking function.

[0282] Step 12:

[0283] The user inputs the desired job requirements into the terminal and sends them to the system.

[0284] Step 13:

[0285] The server collects real-time job information from the job database.

[0286] Step 14:

[0287] The server filters the job information based on the user's conditions and selects the highly suitable ones.

[0288] Step 15:

[0289] The terminal lists the job information obtained from the server and presents the job content and application links to the user.

[0290] (Example 1)

[0291] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0292] In today's labor market, it is difficult for individual users to find the career path that best suits them. Furthermore, there is a lack of consistent support for skill development and efficient job searching. In this context, there is a need for a system that enables users to find suitable occupations, acquire necessary skills, and access job postings quickly.

[0293] 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.

[0294] In this invention, the server includes means for analyzing data on characteristics obtained from the user, means for analyzing external labor market information, and means for obtaining information from external educational resources to generate a learning plan. This allows the user to receive suggestions for the optimal career path, improve necessary skills, and make quick decisions based on the latest job information.

[0295] "User" refers to an individual who uses this system to explore and manage their occupation and career path.

[0296] "Data related to characteristics" refers to information related to the user's personality, interests, work experience, and skills.

[0297] "Means of analysis" refers to methods and processes for using collected data to identify suitable occupations and paths for users.

[0298] "External labor market information" refers to information obtained from external databases regarding current market trends and employment opportunities.

[0299] "Means of analysis" refers to methods for evaluating market information and guiding users to the most suitable occupations and career paths.

[0300] "Educational resources" refer to online courses and learning materials provided to users for skill improvement.

[0301] The "learning plan" refers to a plan that includes specific steps and schedules to support the acquisition of necessary skills in order to achieve the career goals set by the user.

[0302] The "job information" refers to information on job requirements, salary, and job content provided by various companies and organizations.

[0303] The "means of searching" refers to a method of finding appropriate job information from a database based on the user's desired conditions.

[0304] The "means of selection" refers to the process of identifying the optimal job information from the search results and presenting it to the user.

[0305] This invention is an information processing system that supports effective career formation for users through a terminal. The system is mainly composed of a server and a terminal, thereby providing flexible and efficient career management for users.

[0306] What the user does first is to input data regarding personality, interests, experience, and skills via the terminal. The terminal appropriately formats the input information and transmits it to the server. The server uses an analysis engine equipped with AI technology and machine learning algorithms to analyze the received data. Thereby, occupations and career paths suitable for the user are calculated. Specifically, data analysis software operated on a cloud platform or an industry-standard DBMS can be utilized.

[0307] Furthermore, the server acquires the latest labor market information from an external database, integrates it with the analysis results, and generates a learning plan. Based on these information, the server proposes optimal educational resources suitable for the user's career goals and supports skill improvement. Educational resources include online learning platforms and industry-specific online courses.

[0308] Regarding the provision of job information, the server periodically scans external job databases and filters job postings based on the user's skill set and desired conditions. The selected job postings are displayed as a list on the user's terminal, enabling quick application.

[0309] For example, if a user enters "I'm thinking of changing jobs to pursue a marketing position," the server analyzes that information, considers relevant skills and experience, and recommends marketing-specific career paths and educational resources. Furthermore, by providing a list of the latest job postings in the marketing field, users can quickly access and apply for suitable positions.

[0310] An example of a prompt message would be, "I am considering a career change to pursue a marketing position. Given my current skill set and experience, what career paths are possible for me, and what should I study?" This collaborative operation across the entire system allows users to effectively manage their careers and navigate the path to their desired profession.

[0311] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0312] Step 1:

[0313] Users input basic data about their personality, interests, experiences, and skills using their own devices. This data is converted into a structured format such as JSON and prepared to be sent to the server. During this preparation stage, the device checks the integrity of the data and verifies that the entered information is valid.

[0314] Step 2:

[0315] The server analyzes the data received from the terminal. AI technology and machine learning algorithms are used for the analysis. User data, as input, is compared with a database of similar historical profiles and market trends to derive suitable occupations and career paths. As output, appropriate career paths are provided, and this information is sent to the user's terminal.

[0316] Step 3:

[0317] The server retrieves labor market information from an external database and integrates it with the analysis results. This external market information includes industry trends and job postings. In this step, the server considers the market data as input, makes appropriate adjustments to the user's career plan, and generates a learning plan. The learning plan is sent to the user's terminal, presenting a roadmap for specific skill development.

[0318] Step 4:

[0319] The server collects information from external educational resources and builds a learning plan tailored to the user's career goals. This step includes a process of extracting information on appropriate online courses and learning materials based on the entered user data. The learning plan clearly outlines the steps necessary for the user's skill improvement, and progress can be monitored on the device.

[0320] Step 5:

[0321] The system searches for and matches job postings. The server scans external job databases and filters job postings to match the user's specified preferences and skill set. Based on the user's preferences, the system selects the most suitable jobs, and these postings are displayed as a list on the user's terminal. This list includes application links, allowing the user to apply directly.

[0322] Step 6:

[0323] Users utilize information provided by their devices to advance their career development. Based on suggested career paths and learning plans, they acquire skills aligned with their goals and apply for jobs. This step supports the entire process from the user's learning to the evaluation of their progress.

[0324] Each processing step involves the server, terminal, and user working together to create a system that comprehensively supports users in designing their career paths.

[0325] (Application Example 1)

[0326] 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."

[0327] Currently, it is a challenging task for individual users to effectively acquire information about career development and improve their skills in daily life. In particular, finding the optimal occupation and career path based on one's own characteristics and creating and executing a learning plan accordingly requires a great deal of manual work. Furthermore, searching for job postings and obtaining application information must be done individually, which is time-consuming and laborious. Therefore, there is a need for consistent support and automated services to solve these problems.

[0328] 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.

[0329] In this invention, the server includes means for analyzing data on the user's characteristics, interests, experience, and skills acquired from an information processing device, means for analyzing industrial market data imported from an external database, and means for acquiring information in cooperation with home automation equipment and enabling interaction with the user. As a result, the user not only automatically receives individually optimized occupations and career plans, but also receives continuous feedback and progress management through interaction via home automation equipment.

[0330] An "information processing device" is an electronic device that has the ability to receive, process, and transmit digital data, and is used to manage information related to the user.

[0331] "Characteristics" refer to attributes related to a user's personality and behavior, and are the basic information that forms the basis of their individual profile.

[0332] "Interests" refer to the fields and themes that users are particularly interested in and passionate about, and are factors that determine the direction of their career development.

[0333] "Experience" refers to the achievements and knowledge gained through past work and activities, and is an important factor that influences future career choices.

[0334] "Skills" refer to the knowledge and abilities required to perform specific tasks or duties, and are indicators used to measure professional competence.

[0335] "Industrial market data" refers to aggregated external information related to economic activity, such as industry trends and employment conditions, and is used for career recommendations through analysis.

[0336] "Home automation devices" refer to digital devices used for information sharing and automated tasks within the home environment, enabling interaction with the user.

[0337] "Analysis means" refers to technical methods for analyzing data about users using information processing equipment to evaluate vocational aptitude and abilities.

[0338] "Analysis means" refers to the processing steps involved in handling data acquired from external sources and generating information that is useful to the user.

[0339] "Dialogue methods" refer to technologies that enable communication between users and systems, and are necessary to provide continuous support.

[0340] The system for carrying out this invention is constructed using an information processing device, a home automation device, and an external database. The server first acquires data on the user's characteristics, interests, experience, and skills through the information processing device. This data is processed by an analysis engine on the server, which generates the most suitable occupation and career path for the user.

[0341] Furthermore, the server retrieves industry market data from an external database and supplements the analysis results. Based on this information, it identifies the skills the user needs and proposes an optimal learning plan and external educational resources. The home automation device presents the user with acquired information and feedback in real time through interaction. This enables the user to efficiently improve their skills in their daily life.

[0342] Home automation devices also search for employment opportunities based on the user's preferences and provide matching job postings. Users can use this information to quickly proceed with the application process. A specific example of use is a user considering a career change taking a career aptitude test and acquiring new skills through recommended learning courses.

[0343] An example of a prompt using a generative AI model is, "What is the best career path and necessary skills to leverage your current experience and move into a new field?" Based on this prompt, the system provides a specific career development plan tailored to the user.

[0344] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0345] Step 1:

[0346] The server receives data from the information processing device regarding the user's characteristics, interests, experience, and skills. This data includes the user's past work history, educational background, and personality test results. Using this as initial input data, the analysis engine begins processing.

[0347] Step 2:

[0348] The server analyzes the received user data using machine learning algorithms. During the data analysis process, clustering and classification techniques are used to generate user profiles based on their characteristics. This results in the output of suitable occupational categories and career paths for each user.

[0349] Step 3:

[0350] The server retrieves industry market data from an external database. This data includes the latest market trends, in-demand skills, and salary information. The server integrates this data with analysis results to generate job and career information optimized for the user.

[0351] Step 4:

[0352] The server presents this generated occupation and career information through home automation devices. The information presented includes learning plans based on the skill sets the user desires and market popularity. The home automation devices interact with the user and accumulate feedback.

[0353] Step 5:

[0354] Based on the information presented, the user sets their own career goals. The server identifies the necessary skills based on these new goals and suggests external educational resources (e.g., online courses and learning materials). This resource information is presented to the user and incorporated into their learning plan.

[0355] Step 6:

[0356] Based on the user's specified preferences, the server searches an external database for job postings and lists suitable employment opportunities. These listed job postings are then provided to the user via a home automation device, along with an application interface.

[0357] Step 7:

[0358] The server and home automation devices work together to collect user feedback and apply that feedback to improve future career development and job search services. This will enable more personalized information and support for users.

[0359] 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.

[0360] This invention combines an emotion engine with an information processing system that supports users' career development, thereby enabling personalized support that takes into account the user's emotions. This system uses an information processing device to analyze data on the user's personality, interests, experience, and skills, and further analyzes labor market data obtained from an external database to suggest suitable occupations and career paths for the user.

[0361] The server receives text or voice data entered by the user on the device and sends it to the emotion engine. This emotion engine uses natural language processing technology to analyze the user's emotions in real time. For example, if the emotion engine determines that the user is stressed or unmotivated, the system takes this into account and adjusts the career plan, providing advice that includes more encouragement and support.

[0362] Furthermore, the analysis results of this emotion engine are also considered when proposing learning plans. The server analyzes the user's emotional state and adjusts learning resources and progress schedules based on that analysis, thereby reducing the user's burden and supporting efficient and effective skill development. In this way, the system is able to understand the user's overall psychological state and propose a flexible learning plan based on that understanding.

[0363] For example, when a user begins a learning plan to pursue a marketing career, the system uses an emotion engine to initially confirm that the user is highly motivated. The server then sets positive learning goals and tracks progress in detail. However, if a decline in motivation is detected along the way, the server adjusts the learning goals based on the emotion engine's assessment and proposes a revised plan at a less stressful pace for the user. It can also provide messages to boost the user's motivation and offer encouraging topics related to skill acquisition.

[0364] This system allows users to develop a personalized career and improve their skills while reducing emotional burden.

[0365] The following describes the processing flow.

[0366] Step 1:

[0367] Users input information about their personality, interests, experiences, and skills using their devices. They can also input their mood and feelings for the day via voice or text as needed.

[0368] Step 2:

[0369] The terminal sends the entered data and voice / text information to the server.

[0370] Step 3:

[0371] The server passes the user's data to the analysis engine, and the analysis begins. Information about personality, interests, experience, and skills is analyzed based on their respective profiles.

[0372] Step 4:

[0373] The server uses an emotion engine to analyze the user's emotional state from received audio or text data. Natural language processing is employed, and emotional indicators are identified as numerical values ​​or categories.

[0374] Step 5:

[0375] The server generates the optimal occupation and career path for the user based on the analysis results. Occupational suggestions are provided using an approach tailored to the user's emotional state.

[0376] Step 6:

[0377] The server takes into account the emotional state determined by the emotion engine and adjusts the tone of messages and suggestions to the user as needed.

[0378] Step 7:

[0379] The device receives carrier suggestions and messages from the server and displays them to the user.

[0380] Step 8:

[0381] The user inputs their career goals and desired skill set from their device and sends it to the server.

[0382] Step 9:

[0383] The server identifies the skills required by the user based on their career goals. This process includes a gap analysis between the current skill level and market needs.

[0384] Step 10:

[0385] The server takes into account the analysis results from the emotion engine and customizes and proposes a learning plan in a way that reduces the user's psychological burden.

[0386] Step 11:

[0387] The device displays the generated learning plan to the user and provides a function to continuously track their progress.

[0388] Step 12:

[0389] The server periodically updates job data and filters job postings in real time to match the user's desired conditions.

[0390] Step 13:

[0391] The terminal displays job postings received from the server to the user and provides a link to apply.

[0392] In this way, the system comprehensively supports career development while taking into account the user's emotional state.

[0393] (Example 2)

[0394] 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".

[0395] In today's professional environment, there is a demand for prompt and appropriate suggestions of occupations and career paths tailored to individual clients. However, traditional methods often fail to consider the emotional state of each client, resulting in proposed career plans that are not always suitable for their psychological condition. This can lead to decreased motivation and insufficient results in skill development and career choices.

[0396] 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.

[0397] In this invention, the server includes means for interpreting information about the user's characteristics, interests, experiences, and abilities; means for analyzing employment market information collected from external sources; and means for analyzing the user's emotional state using an emotion engine and adjusting career paths based on that analysis. This enables the suggestion of personalized, emotion-responsive occupational and career plans to the user.

[0398] An "information processing system" is a device that collects and processes user characteristics and external information to perform data analysis and make suggestions.

[0399] "Information sources" refer to external databases or data feeds that provide data on the employment market.

[0400] "Characteristics" refer to the individual features that make up a user's personality and behavioral patterns.

[0401] "Interest" refers to the things that users are interested in or concerned with.

[0402] "Experience" is the accumulation of things that a user has learned and experienced in the past.

[0403] "Ability" refers to the technical or specialized skills and knowledge that the user possesses.

[0404] The "emotion engine" is a program based on natural language processing technology that analyzes user input data and evaluates their emotional state.

[0405] A "career path" refers to a plan that outlines the occupations a user can pursue and the direction of their career development.

[0406] "Personalized advice" refers to advice provided based on the user's unique circumstances and feelings.

[0407] To implement this invention, an information processing system equipped with an emotion engine is required. The server first receives text or voice data from the user via a terminal. This data includes the user's characteristics, interests, experiences, abilities, and current emotional state. Next, the server passes the received data to the emotion engine, which analyzes the user's emotional state in real time. This analysis utilizes natural language processing technology, such as using libraries like the Google Natural Language API.

[0408] The server analyzes the latest job market information obtained from external sources based on the analysis results. This analysis utilizes Apache Hadoop and other commonly used big data processing platforms. This generates suitable occupations and career paths for the user and provides advice. During this process, a career plan generated using a generative AI model is presented to the user.

[0409] For example, if a user enters "I'm interested in digital marketing" into their device, the server sends this information to the emotion engine and data analysis engine to develop an optimal career plan. If high stress levels are detected in the user, the server provides a flexible learning plan to alleviate that pressure. An example of a prompt would be, "Please create a learning plan for a marketing career. Include content that reduces user stress and increases motivation."

[0410] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0411] Step 1:

[0412] Users input text or voice data about their occupation and career through their device. This input data includes the user's characteristics, interests, experience, and abilities. The device then transmits this data to the server.

[0413] Step 2:

[0414] The server sends the received data to the emotion engine. The emotion engine uses natural language processing technology to analyze the user's input data in real time and evaluate their emotional state. Specifically, it determines the user's stress level and motivation based on emotional indicators extracted from the text. It generates data indicating the emotional state as output.

[0415] Step 3:

[0416] The server analyzes the analyzed emotional state data and the user's characteristics, interests, experiences, and abilities, along with the latest job market information obtained from external sources. Specifically, it uses big data processing tools to identify the most suitable occupations and career paths for the user. This analysis generates a list of candidate occupations and career paths to suggest to the user.

[0417] Step 4:

[0418] The server creates a career plan optimized for the user based on the generated list of candidate career paths and the user's emotional state. A generative AI model is used to generate a customized plan tailored to the user's needs and emotional state. The output includes a career plan with specific job suggestions and a learning plan.

[0419] Step 5:

[0420] The server sends the final generated career plan to the terminal and presents it to the user. Based on the information presented, the user can decide on future career choices and actions for skill development. If feedback or further suggestions are needed, the system takes this into account and adjusts the plan accordingly.

[0421] (Application Example 2)

[0422] 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."

[0423] Traditional career development support systems provided job suggestions based on users' personality and skill data, but they failed to consider changes in users' emotions and motivation, resulting in insufficient personalized support. Furthermore, they were unable to dynamically adjust learning plans based on users' daily emotions, making efficient skill improvement difficult.

[0424] 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.

[0425] In this invention, the server includes means for analyzing data on the user's personality, interests, experiences, and skills acquired from an information processing device; means for analyzing labor market data imported from an external database; and means for analyzing the user's emotional state in real time using an emotion analysis engine and making adjustments to the generated occupation and career path based on the emotional information. This enables the provision of personalized career plans tailored to each user's emotional state and the dynamic adjustment of effective learning plans.

[0426] An "information processing device" is a system for acquiring and analyzing data related to a user's personality, interests, experiences, and skills.

[0427] An "external database" is a data storage system that accumulates information about the labor market and allows this information to be imported for analysis.

[0428] An "emotion analysis engine" is an analysis system equipped with technology that determines the emotional state of a user in real time based on text and voice data acquired from them.

[0429] A "career path" is a plan that outlines suitable occupations for the user and the career development process leading up to them.

[0430] A "learning plan" is a plan that includes a procedure and resource allocation aimed at acquiring the skills necessary to achieve the occupational goals set by the user.

[0431] "Adjustment" refers to the process of dynamically modifying plans and proposals based on the user's current emotional state and progress.

[0432] "Job postings" refer to data on employment opportunities obtained from the labor market, including details of jobs that users can apply for.

[0433] The system for implementing this invention aims to provide users with career development support optimized for their needs. This system functions as an information processing device, an external database, and an emotion analysis engine.

[0434] The server retrieves data on the user's personality, interests, experience, and skills from an information processing device. By analyzing this data, it gains a detailed understanding of the user's characteristics. In addition, the server imports labor market data from an external database and analyzes it to generate suitable occupations and career paths for the user.

[0435] Furthermore, the emotion analysis engine processes the user's input text and voice data in real time to determine their emotional state. Specifically, it uses natural language processing technology to analyze text and capture changes in emotions and motivation. For example, it can utilize natural language processing libraries using Python (such as NLTK or spaCy).

[0436] Based on the results of emotion analysis, the server dynamically adjusts the career path and learning plan. This enables flexible support tailored to the user's emotional state and progress. Furthermore, hardware devices equipped with microphones and speakers can be used, allowing for voice data input and interaction.

[0437] As a concrete example, if a user reports work-related stress on a given day, the system recognizes that emotion through emotion analysis and proposes new relaxing activities in the learning plan. An example of a related generative AI model prompt is as follows:

[0438] "When a user is feeling stressed, what suggestions do you offer? Please include relaxation methods as well."

[0439] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0440] Step 1:

[0441] The user inputs text or voice data into the device. The device receives this data and converts it into digital data. This data is then sent to the server as input.

[0442] Step 2:

[0443] The server processes the received digital data using an information processing device. Specifically, it utilizes natural language processing technology to analyze the user's personality, interests, experiences, and skills, and generates a personality profile. This profile is then output.

[0444] Step 3:

[0445] The server accesses an external database to retrieve current labor market data. This data includes various information about occupations. The information retrieved from the database is analyzed as input, and the results of the labor market trend analysis are output.

[0446] Step 4:

[0447] The server integrates the generated personality profile with analyzed labor market information. Based on this, it generates suitable occupations and career paths for the user. Personalized career suggestions are output using the generated AI model.

[0448] Step 5:

[0449] The received text or audio data is sent to the sentiment analysis engine. The sentiment analysis engine uses natural language processing to analyze the data and determine the user's real-time emotional state. The emotional information obtained during this process is then output.

[0450] Step 6:

[0451] The server dynamically adjusts the generated carrier path based on emotional information. By incorporating emotional support elements, it redesigns the carrier plan to better suit the user. This redesigned plan is then output.

[0452] Step 7:

[0453] The system presents users with redesigned career paths and learning plans via their devices. Furthermore, it offers suggestions for relaxation and motivation enhancement. In this process, it utilizes prompts from a generated AI model to ensure optimal communication.

[0454] 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.

[0455] 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.

[0456] 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.

[0457] [Third Embodiment]

[0458] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0459] 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.

[0460] 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).

[0461] 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.

[0462] 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.

[0463] 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).

[0464] 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.

[0465] 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.

[0466] 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.

[0467] 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.

[0468] 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.

[0469] 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".

[0470] This invention provides an information processing system that enables users to effectively develop their careers. This system includes functions that comprehensively support self-analysis, aptitude testing, skill development support, and job matching. Specific embodiments are described below.

[0471] The server first receives information about the user's personality, interests, experience, and skills entered through their terminal. Based on this, the analysis engine on the server automatically analyzes the data and calculates suitable occupations and career paths for the user. This process utilizes machine learning algorithms and is optimized by considering similar past profiles and current market trends. The analysis results are displayed on the terminal, and the user can receive feedback.

[0472] Furthermore, the server identifies the necessary skills based on the user's set career goals and generates a learning plan that aligns with market trends. In this process, it incorporates external educational resources and online course information to present the user with the most suitable learning path. By receiving this, users can gradually improve their skills. Their progress is tracked through their device, contributing to increased motivation.

[0473] Regarding job matching, the server periodically collects the latest information from external job databases and matches users based on their desired conditions and skill sets. This result is displayed on the user's device as a list of job postings, showing the job description, conditions, and application link. This allows users to quickly access suitable jobs and proceed with the application process.

[0474] For example, if a user wishes to switch careers to a marketing position and enters their current experience and required skills via their device, the server will analyze the information, recommend online courses suitable for a marketing major, and present a trial career path. At the same time, it will filter and provide currently available marketing-related job postings. In this way, users can receive consistent support at every stage of their career development and quickly obtain the information and means to achieve their goals.

[0475] The following describes the processing flow.

[0476] Step 1:

[0477] Users use their devices to input information about their personality, interests, experiences, and skills into a self-assessment questionnaire.

[0478] Step 2:

[0479] The terminal sends the entered information to the server.

[0480] Step 3:

[0481] The server passes the user data it receives to the analysis engine, which then begins the analysis using natural language processing.

[0482] Step 4:

[0483] The server uses machine learning algorithms to compare the user's profile with similar historical data.

[0484] Step 5:

[0485] The server calculates suitable occupations and career paths for the user based on the analysis results and sends the results to the terminal.

[0486] Step 6:

[0487] The terminal receives data from the server and displays the analysis results on the user interface.

[0488] Step 7:

[0489] Users set career goals and input the skills they aim to acquire and the knowledge they want to learn into the device.

[0490] Step 8:

[0491] The terminal sends user input to the server.

[0492] Step 9:

[0493] The server references a market database to identify the necessary skills related to the career goals.

[0494] Step 10:

[0495] The system evaluates the gap between the server's required skills and the user's current skills, and generates a learning plan to bridge that gap.

[0496] Step 11:

[0497] The device displays the learning plan received from the server on the user's dashboard, providing a progress tracking function.

[0498] Step 12:

[0499] The user enters their desired job requirements into a terminal and sends them to the system.

[0500] Step 13:

[0501] The server collects job information from the job database in real time.

[0502] Step 14:

[0503] The server filters job postings based on the user's criteria and selects those with the highest degree of suitability.

[0504] Step 15:

[0505] The terminal displays a list of job postings retrieved from the server and presents the job description and application link to the user.

[0506] (Example 1)

[0507] 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."

[0508] In today's labor market, it is difficult for individual users to find the career path that best suits them. Furthermore, there is a lack of consistent support for skill development and efficient job searching. In this context, there is a need for a system that enables users to find suitable occupations, acquire necessary skills, and access job postings quickly.

[0509] 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.

[0510] In this invention, the server includes means for analyzing data on characteristics obtained from the user, means for analyzing external labor market information, and means for obtaining information from external educational resources to generate a learning plan. This allows the user to receive suggestions for the optimal career path, improve necessary skills, and make quick decisions based on the latest job information.

[0511] "User" refers to an individual who uses this system to explore and manage their occupation and career path.

[0512] "Data related to characteristics" refers to information related to the user's personality, interests, work experience, and skills.

[0513] "Means of analysis" refers to methods and processes for using collected data to identify suitable occupations and paths for users.

[0514] "External labor market information" refers to information obtained from external databases regarding current market trends and employment opportunities.

[0515] "Means of analysis" refers to methods for evaluating market information and guiding users to the most suitable occupations and career paths.

[0516] "Educational resources" refer to online courses and learning materials provided to users for skill improvement.

[0517] A "learning plan" refers to a plan that includes specific steps and schedules to support the acquisition of necessary skills in order to achieve the professional goals set by the user.

[0518] "Job postings" refer to information provided by various companies and organizations regarding job requirements, salaries, and job descriptions.

[0519] "Search methods" refer to the methods used to find suitable job postings from a database based on the user's desired conditions.

[0520] "Selection method" refers to the process of identifying the most suitable job postings from search results and presenting them to the user.

[0521] This invention is an information processing system that supports users in effectively forming their careers through terminals. The system mainly consists of a server and terminals, thereby providing users with flexible and efficient career management.

[0522] The user's first step is to input data about their personality, interests, experience, and skills via a device. The device then formats the input information appropriately and sends it to the server. The server uses an analysis engine equipped with AI technology and machine learning algorithms to analyze the received data. This calculates suitable occupations and career paths for the user. Specifically, data analysis software operating on a cloud platform or industry-standard DBMS can be used.

[0523] Furthermore, the server retrieves the latest labor market information from external databases and integrates it with the analysis results to generate a learning plan. Based on this information, the server suggests optimal educational resources tailored to the user's career goals and supports skill improvement. These educational resources include online learning platforms and industry-specific online courses.

[0524] Regarding the provision of job information, the server periodically scans external job databases and filters job postings based on the user's skill set and desired conditions. The selected job postings are displayed as a list on the user's terminal, enabling quick application.

[0525] For example, if a user enters "I'm thinking of changing jobs to pursue a marketing position," the server analyzes that information, considers relevant skills and experience, and recommends marketing-specific career paths and educational resources. Furthermore, by providing a list of the latest job postings in the marketing field, users can quickly access and apply for suitable positions.

[0526] An example of a prompt message would be, "I am considering a career change to pursue a marketing position. Given my current skill set and experience, what career paths are possible for me, and what should I study?" This collaborative operation across the entire system allows users to effectively manage their careers and navigate the path to their desired profession.

[0527] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0528] Step 1:

[0529] Users input basic data about their personality, interests, experiences, and skills using their own devices. This data is converted into a structured format such as JSON and prepared to be sent to the server. During this preparation stage, the device checks the integrity of the data and verifies that the entered information is valid.

[0530] Step 2:

[0531] The server analyzes the data received from the terminal. AI technology and machine learning algorithms are used for the analysis. User data, as input, is compared with a database of similar historical profiles and market trends to derive suitable occupations and career paths. As output, appropriate career paths are provided, and this information is sent to the user's terminal.

[0532] Step 3:

[0533] The server retrieves labor market information from an external database and integrates it with the analysis results. This external market information includes industry trends and job postings. In this step, the server considers the market data as input, makes appropriate adjustments to the user's career plan, and generates a learning plan. The learning plan is sent to the user's terminal, presenting a roadmap for specific skill development.

[0534] Step 4:

[0535] The server collects information from external educational resources and builds a learning plan tailored to the user's career goals. This step includes a process of extracting information on appropriate online courses and learning materials based on the entered user data. The learning plan clearly outlines the steps necessary for the user's skill improvement, and progress can be monitored on the device.

[0536] Step 5:

[0537] The system searches for and matches job postings. The server scans external job databases and filters job postings to match the user's specified preferences and skill set. Based on the user's preferences, the system selects the most suitable jobs, and these postings are displayed as a list on the user's terminal. This list includes application links, allowing the user to apply directly.

[0538] Step 6:

[0539] Users utilize information provided by their devices to advance their career development. Based on suggested career paths and learning plans, they acquire skills aligned with their goals and apply for jobs. This step supports the entire process from the user's learning to the evaluation of their progress.

[0540] Each processing step involves the server, terminal, and user working together to create a system that comprehensively supports users in designing their career paths.

[0541] (Application Example 1)

[0542] 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."

[0543] Currently, it is a challenging task for individual users to effectively acquire information about career development and improve their skills in daily life. In particular, finding the optimal occupation and career path based on one's own characteristics and creating and executing a learning plan accordingly requires a great deal of manual work. Furthermore, searching for job postings and obtaining application information must be done individually, which is time-consuming and laborious. Therefore, there is a need for consistent support and automated services to solve these problems.

[0544] 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.

[0545] In this invention, the server includes means for analyzing data on the user's characteristics, interests, experience, and skills acquired from an information processing device, means for analyzing industrial market data imported from an external database, and means for acquiring information in cooperation with home automation equipment and enabling interaction with the user. As a result, the user not only automatically receives individually optimized occupations and career plans, but also receives continuous feedback and progress management through interaction via home automation equipment.

[0546] An "information processing device" is an electronic device that has the ability to receive, process, and transmit digital data, and is used to manage information related to the user.

[0547] "Characteristics" refer to attributes related to a user's personality and behavior, and are the basic information that forms the basis of their individual profile.

[0548] "Interests" refer to the fields and themes that users are particularly interested in and passionate about, and are factors that determine the direction of their career development.

[0549] "Experience" refers to the achievements and knowledge gained through past work and activities, and is an important factor that influences future career choices.

[0550] "Skills" refer to the knowledge and abilities required to perform specific tasks or duties, and are indicators used to measure professional competence.

[0551] "Industrial market data" refers to aggregated external information related to economic activity, such as industry trends and employment conditions, and is used for career recommendations through analysis.

[0552] "Home automation devices" refer to digital devices used for information sharing and automated tasks within a home environment, enabling interaction with the user.

[0553] "Analysis means" refers to technical methods for analyzing data about users using information processing equipment to evaluate vocational aptitude and abilities.

[0554] "Analysis means" refers to the processing steps involved in handling data acquired from external sources and generating information that is useful to the user.

[0555] "Dialogue methods" refer to technologies that enable communication between users and systems, and are necessary to provide continuous support.

[0556] The system for carrying out this invention is constructed using an information processing device, a home automation device, and an external database. The server first acquires data on the user's characteristics, interests, experience, and skills through the information processing device. This data is processed by an analysis engine on the server, which generates the most suitable occupation and career path for the user.

[0557] Furthermore, the server retrieves industry market data from an external database and supplements the analysis results. Based on this information, it identifies the skills the user needs and proposes an optimal learning plan and external educational resources. The home automation device presents the user with acquired information and feedback in real time through interaction. This enables the user to efficiently improve their skills in their daily life.

[0558] Home automation devices also search for employment opportunities based on the user's preferences and provide matching job postings. Users can use this information to quickly proceed with the application process. A specific example of use is a user considering a career change taking a career aptitude test and acquiring new skills through recommended learning courses.

[0559] An example of a prompt using a generative AI model is, "What is the best career path and necessary skills to leverage your current experience and move into a new field?" Based on this prompt, the system provides a specific career development plan tailored to the user.

[0560] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0561] Step 1:

[0562] The server receives data from the information processing device regarding the user's characteristics, interests, experience, and skills. This data includes the user's past work history, educational background, and personality test results. Using this as initial input data, the analysis engine begins processing.

[0563] Step 2:

[0564] The server analyzes the received user data using machine learning algorithms. During the data analysis process, clustering and classification techniques are used to generate user profiles based on their characteristics. This results in the output of suitable occupational categories and career paths for each user.

[0565] Step 3:

[0566] The server retrieves industry market data from an external database. This data includes the latest market trends, in-demand skills, and salary information. The server integrates this data with analysis results to generate job and career information optimized for the user.

[0567] Step 4:

[0568] The server presents this generated occupation and career information through home automation devices. The information presented includes learning plans based on the skill sets the user desires and market popularity. The home automation devices interact with the user and accumulate feedback.

[0569] Step 5:

[0570] Based on the information presented, the user sets their own career goals. The server identifies the necessary skills based on these new goals and suggests external educational resources (e.g., online courses and learning materials). This resource information is presented to the user and incorporated into their learning plan.

[0571] Step 6:

[0572] Based on the user's specified preferences, the server searches an external database for job postings and lists suitable employment opportunities. These listed job postings are then provided to the user via a home automation device, along with an application interface.

[0573] Step 7:

[0574] The server and home automation devices work together to collect user feedback and apply that feedback to improve future career development and job search services. This will enable more personalized information and support for users.

[0575] 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.

[0576] This invention combines an emotion engine with an information processing system that supports users' career development, thereby enabling personalized support that takes into account the user's emotions. This system uses an information processing device to analyze data on the user's personality, interests, experience, and skills, and further analyzes labor market data obtained from an external database to suggest suitable occupations and career paths for the user.

[0577] The server receives text or voice data entered by the user on the device and sends it to the emotion engine. This emotion engine uses natural language processing technology to analyze the user's emotions in real time. For example, if the emotion engine determines that the user is stressed or unmotivated, the system takes this into account and adjusts the career plan, providing advice that includes more encouragement and support.

[0578] Furthermore, the analysis results of this emotion engine are also considered when proposing learning plans. The server analyzes the user's emotional state and adjusts learning resources and progress schedules based on that analysis, thereby reducing the user's burden and supporting efficient and effective skill development. In this way, the system is able to understand the user's overall psychological state and propose a flexible learning plan based on that understanding.

[0579] For example, when a user begins a learning plan to pursue a marketing career, the system uses an emotion engine to initially confirm that the user is highly motivated. The server then sets positive learning goals and tracks progress in detail. However, if a decline in motivation is detected along the way, the server adjusts the learning goals based on the emotion engine's assessment and proposes a revised plan at a less stressful pace for the user. It can also provide messages to boost the user's motivation and offer encouraging topics related to skill acquisition.

[0580] This system allows users to develop a personalized career and improve their skills while reducing emotional burden.

[0581] The following describes the processing flow.

[0582] Step 1:

[0583] Users input information about their personality, interests, experiences, and skills using their devices. They can also input their mood and feelings for the day via voice or text as needed.

[0584] Step 2:

[0585] The terminal sends the entered data and voice / text information to the server.

[0586] Step 3:

[0587] The server passes the user's data to the analysis engine, and the analysis begins. Information about personality, interests, experience, and skills is analyzed based on their respective profiles.

[0588] Step 4:

[0589] The server uses an emotion engine to analyze the user's emotional state from received audio or text data. Natural language processing is employed, and emotional indicators are identified as numerical values ​​or categories.

[0590] Step 5:

[0591] The server generates the optimal occupation and career path for the user based on the analysis results. Occupational suggestions are provided using an approach tailored to the user's emotional state.

[0592] Step 6:

[0593] The server takes into account the emotional state determined by the emotion engine and adjusts the tone of messages and suggestions to the user as needed.

[0594] Step 7:

[0595] The device receives carrier suggestions and messages from the server and displays them to the user.

[0596] Step 8:

[0597] The user inputs their career goals and desired skill set from their device and sends it to the server.

[0598] Step 9:

[0599] The server identifies the skills required by the user based on their professional goals. This process includes a gap analysis between the current skill level and market needs.

[0600] Step 10:

[0601] The server takes into account the analysis results from the emotion engine and customizes and proposes a learning plan in a way that reduces the user's psychological burden.

[0602] Step 11:

[0603] The device displays the generated learning plan to the user and provides a function to continuously track their progress.

[0604] Step 12:

[0605] The server periodically updates job data and filters job postings in real time to match the user's desired conditions.

[0606] Step 13:

[0607] The terminal displays job postings received from the server to the user and provides a link to apply.

[0608] In this way, the system comprehensively supports career development while taking into account the user's emotional state.

[0609] (Example 2)

[0610] 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."

[0611] In today's professional environment, there is a demand for prompt and appropriate job and career path suggestions tailored to individual clients. However, traditional methods often fail to consider the individual emotional state of clients, resulting in proposed career plans that are not always suitable for their psychological condition. This can lead to decreased motivation and insufficient results in skill development and career choices.

[0612] 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.

[0613] In this invention, the server includes means for interpreting information about the user's characteristics, interests, experiences, and abilities; means for analyzing employment market information collected from external sources; and means for analyzing the user's emotional state using an emotion engine and adjusting career paths based on that analysis. This makes it possible to propose personalized, emotion-responsive occupational and career plans to the user.

[0614] An "information processing system" is a device that collects and processes user characteristics and external information to perform data analysis and make suggestions.

[0615] "Information sources" refer to external databases or data feeds that provide data on the employment market.

[0616] "Characteristics" refer to the individual features that make up a user's personality and behavioral patterns.

[0617] "Interest" refers to the things that users are interested in or concerned with.

[0618] "Experience" is the accumulation of things that a user has learned and experienced in the past.

[0619] "Ability" refers to the technical or specialized skills and knowledge that the user possesses.

[0620] The "emotion engine" is a program based on natural language processing technology that analyzes user input data and evaluates their emotional state.

[0621] A "career path" refers to a plan that outlines the occupations a user can pursue and the direction of their career development.

[0622] "Personalized advice" refers to advice provided based on the user's unique circumstances and feelings.

[0623] To implement this invention, an information processing system equipped with an emotion engine is required. The server first receives text or voice data from the user via a terminal. This data includes the user's characteristics, interests, experiences, abilities, and current emotional state. Next, the server passes the received data to the emotion engine, which analyzes the user's emotional state in real time. This analysis utilizes natural language processing technology, such as using libraries like the Google Natural Language API.

[0624] The server analyzes the latest job market information obtained from external sources based on the analysis results. This analysis utilizes Apache Hadoop and other commonly used big data processing platforms. This generates suitable occupations and career paths for the user and provides advice. During this process, a career plan generated using a generative AI model is presented to the user.

[0625] For example, if a user enters "I'm interested in digital marketing" into their device, the server sends this information to the emotion engine and data analysis engine to develop an optimal career plan. If high stress levels are detected in the user, the server provides a flexible learning plan to alleviate that pressure. An example of a prompt would be, "Please create a learning plan for a marketing career. Include content that reduces user stress and increases motivation."

[0626] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0627] Step 1:

[0628] Users input text or voice data about their occupation and career through their device. This input data includes the user's characteristics, interests, experience, and abilities. The device then transmits this data to the server.

[0629] Step 2:

[0630] The server sends the received data to the emotion engine. The emotion engine uses natural language processing technology to analyze the user's input data in real time and evaluate their emotional state. Specifically, it determines the user's stress level and motivation based on emotional indicators extracted from the text. It generates data indicating the emotional state as output.

[0631] Step 3:

[0632] The server analyzes the analyzed emotional state data and the user's characteristics, interests, experiences, and abilities, along with the latest job market information obtained from external sources. Specifically, it uses big data processing tools to identify the most suitable occupations and career paths for the user. This analysis generates a list of candidate occupations and career paths to suggest to the user.

[0633] Step 4:

[0634] The server creates a career plan optimized for the user based on the generated list of candidate career paths and the user's emotional state. A generative AI model is used to generate a customized plan tailored to the user's needs and emotional state. The output includes a career plan with specific job suggestions and a learning plan.

[0635] Step 5:

[0636] The server sends the final generated career plan to the terminal and presents it to the user. Based on the information presented, the user can decide on future career choices and actions for skill development. If feedback or further suggestions are needed, the system takes this into account and adjusts the plan accordingly.

[0637] (Application Example 2)

[0638] 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."

[0639] Traditional career development support systems provided job suggestions based on users' personality and skill data, but they failed to consider changes in users' emotions and motivation, resulting in insufficient personalized support. Furthermore, they were unable to dynamically adjust learning plans based on users' daily emotions, making efficient skill improvement difficult.

[0640] 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.

[0641] In this invention, the server includes means for analyzing data on the user's personality, interests, experiences, and skills acquired from an information processing device; means for analyzing labor market data imported from an external database; and means for analyzing the user's emotional state in real time using an emotion analysis engine and making adjustments to the generated occupation and career path based on the emotional information. This enables the provision of personalized career plans tailored to each user's emotional state and the dynamic adjustment of effective learning plans.

[0642] An "information processing device" is a system for acquiring and analyzing data related to a user's personality, interests, experiences, and skills.

[0643] An "external database" is a data storage system that accumulates information about the labor market and allows this information to be imported for analysis.

[0644] An "emotion analysis engine" is an analysis system equipped with technology that determines the emotional state of a user in real time based on text and voice data acquired from them.

[0645] A "career path" is a plan that outlines suitable occupations for the user and the career development process leading up to them.

[0646] A "learning plan" is a plan that includes a procedure and resource allocation aimed at acquiring the skills necessary to achieve the occupational goals set by the user.

[0647] "Adjustment" refers to the process of dynamically modifying plans and proposals based on the user's current emotional state and progress.

[0648] "Job postings" refer to data on employment opportunities obtained from the labor market, including details of jobs that users can apply for.

[0649] The system for implementing this invention aims to provide users with career development support optimized for their needs. This system functions as an information processing device, an external database, and an emotion analysis engine.

[0650] The server retrieves data on the user's personality, interests, experience, and skills from an information processing device. By analyzing this data, it gains a detailed understanding of the user's characteristics. In addition, the server imports labor market data from an external database and analyzes it to generate suitable occupations and career paths for the user.

[0651] Furthermore, the emotion analysis engine processes the user's input text and voice data in real time to determine their emotional state. Specifically, it uses natural language processing technology to analyze text and capture changes in emotions and motivation. For example, it can utilize natural language processing libraries using Python (such as NLTK or spaCy).

[0652] Based on the results of emotion analysis, the server dynamically adjusts the career path and learning plan. This enables flexible support tailored to the user's emotional state and progress. Furthermore, hardware devices equipped with microphones and speakers can be used, allowing for voice data input and interaction.

[0653] As a concrete example, if a user reports work-related stress on a given day, the system recognizes that emotion through emotion analysis and proposes new relaxing activities in the learning plan. An example of a related generative AI model prompt is as follows:

[0654] "When a user is feeling stressed, what suggestions do you offer? Please include relaxation methods as well."

[0655] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0656] Step 1:

[0657] The user inputs text or voice data into the device. The device receives this data and converts it into digital data. This data is then sent to the server as input.

[0658] Step 2:

[0659] The server processes the received digital data using an information processing device. Specifically, it utilizes natural language processing technology to analyze the user's personality, interests, experiences, and skills, and generates a personality profile. This profile is then output.

[0660] Step 3:

[0661] The server accesses an external database to retrieve current labor market data. This data includes various information about occupations. The information retrieved from the database is analyzed as input, and the results of the labor market trend analysis are output.

[0662] Step 4:

[0663] The server integrates the generated personality profile with analyzed labor market information. Based on this, it generates suitable occupations and career paths for the user. Personalized career suggestions are output using the generated AI model.

[0664] Step 5:

[0665] The received text or audio data is sent to the sentiment analysis engine. The sentiment analysis engine uses natural language processing to analyze the data and determine the user's real-time emotional state. The emotional information obtained during this process is then output.

[0666] Step 6:

[0667] The server dynamically adjusts the generated carrier path based on emotional information. By incorporating emotional support elements, it redesigns the carrier plan to better suit the user. This redesigned plan is then output.

[0668] Step 7:

[0669] The system presents users with redesigned career paths and learning plans via their devices. Furthermore, it offers suggestions for relaxation and motivation enhancement. In this process, it utilizes prompts from a generated AI model to ensure optimal communication.

[0670] 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.

[0671] 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.

[0672] 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.

[0673] [Fourth Embodiment]

[0674] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0675] 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.

[0676] 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).

[0677] 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.

[0678] 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.

[0679] 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).

[0680] 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.

[0681] 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.

[0682] 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.

[0683] 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.

[0684] 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.

[0685] 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.

[0686] 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".

[0687] This invention provides an information processing system that enables users to effectively develop their careers. This system includes functions that comprehensively support self-analysis, aptitude testing, skill development support, and job matching. Specific embodiments are described below.

[0688] The server first receives information about the user's personality, interests, experience, and skills entered through their terminal. Based on this, the analysis engine on the server automatically analyzes the data and calculates suitable occupations and career paths for the user. This process utilizes machine learning algorithms and is optimized by considering similar past profiles and current market trends. The analysis results are displayed on the terminal, and the user can receive feedback.

[0689] Furthermore, the server identifies the necessary skills based on the user's set career goals and generates a learning plan that aligns with market trends. In this process, it incorporates external educational resources and online course information to present the user with the most suitable learning path. By receiving this, users can gradually improve their skills. Their progress is tracked through their device, contributing to increased motivation.

[0690] Regarding job matching, the server periodically collects the latest information from external job databases and matches users based on their desired conditions and skill sets. This result is displayed on the user's device as a list of job postings, showing the job description, conditions, and application link. This allows users to quickly access suitable jobs and proceed with the application process.

[0691] For example, if a user wishes to switch careers to a marketing position and enters their current experience and required skills via their device, the server will analyze the information, recommend online courses suitable for a marketing major, and present a trial career path. At the same time, it will filter and provide currently available marketing-related job postings. In this way, users can receive consistent support at every stage of their career development and quickly obtain the information and means to achieve their goals.

[0692] The following describes the processing flow.

[0693] Step 1:

[0694] Users use their devices to input information about their personality, interests, experiences, and skills into a self-assessment questionnaire.

[0695] Step 2:

[0696] The terminal sends the entered information to the server.

[0697] Step 3:

[0698] The server passes the user data it receives to the analysis engine, which then begins the analysis using natural language processing.

[0699] Step 4:

[0700] The server uses machine learning algorithms to compare the user's profile with similar historical data.

[0701] Step 5:

[0702] The server calculates suitable occupations and career paths for the user based on the analysis results and sends the results to the terminal.

[0703] Step 6:

[0704] The terminal receives data from the server and displays the analysis results on the user interface.

[0705] Step 7:

[0706] Users set career goals and input the skills they aim to acquire and the knowledge they want to learn into the device.

[0707] Step 8:

[0708] The terminal sends user input to the server.

[0709] Step 9:

[0710] The server references a market database to identify the necessary skills related to the career goals.

[0711] Step 10:

[0712] The system evaluates the gap between the server's required skills and the user's current skills, and generates a learning plan to bridge that gap.

[0713] Step 11:

[0714] The device displays the learning plan received from the server on the user's dashboard, providing a progress tracking function.

[0715] Step 12:

[0716] The user enters their desired job requirements into a terminal and sends them to the system.

[0717] Step 13:

[0718] The server collects job information from the job database in real time.

[0719] Step 14:

[0720] The server filters job postings based on the user's criteria and selects those with the highest degree of suitability.

[0721] Step 15:

[0722] The terminal displays a list of job postings retrieved from the server and presents the job description and application link to the user.

[0723] (Example 1)

[0724] 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".

[0725] In today's labor market, it is difficult for individual users to find the career path that best suits them. Furthermore, there is a lack of consistent support for skill development and efficient job searching. In this context, there is a need for a system that enables users to find suitable occupations, acquire necessary skills, and access job postings quickly.

[0726] 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.

[0727] In this invention, the server includes means for analyzing data on characteristics obtained from the user, means for analyzing external labor market information, and means for obtaining information from external educational resources to generate a learning plan. This allows the user to receive suggestions for the optimal career path, improve necessary skills, and make quick decisions based on the latest job information.

[0728] "User" refers to an individual who uses this system to explore and manage their occupation and career path.

[0729] "Data related to characteristics" refers to information related to the user's personality, interests, work experience, and skills.

[0730] "Means of analysis" refers to methods and processes for using collected data to identify suitable occupations and paths for users.

[0731] "External labor market information" refers to information obtained from external databases regarding current market trends and employment opportunities.

[0732] "Means of analysis" refers to methods for evaluating market information and guiding users to the most suitable occupations and career paths.

[0733] "Educational resources" refer to online courses and learning materials provided to users for skill improvement.

[0734] A "learning plan" refers to a plan that includes specific steps and schedules to support the acquisition of necessary skills in order to achieve the professional goals set by the user.

[0735] "Job postings" refer to information provided by various companies and organizations regarding job requirements, salaries, and job descriptions.

[0736] "Search methods" refer to the methods used to find suitable job postings from a database based on the user's desired conditions.

[0737] "Selection method" refers to the process of identifying the most suitable job postings from search results and presenting them to the user.

[0738] This invention is an information processing system that supports users in effectively forming their careers through terminals. The system mainly consists of a server and terminals, thereby providing users with flexible and efficient career management.

[0739] The user's first step is to input data about their personality, interests, experience, and skills via a device. The device then formats the input information appropriately and sends it to the server. The server uses an analysis engine equipped with AI technology and machine learning algorithms to analyze the received data. This calculates suitable occupations and career paths for the user. Specifically, data analysis software operating on a cloud platform or industry-standard DBMS can be used.

[0740] Furthermore, the server retrieves the latest labor market information from external databases and integrates it with the analysis results to generate a learning plan. Based on this information, the server suggests optimal educational resources tailored to the user's career goals and supports skill improvement. These educational resources include online learning platforms and industry-specific online courses.

[0741] Regarding the provision of job information, the server periodically scans external job databases and filters job postings based on the user's skill set and desired conditions. The selected job postings are displayed as a list on the user's terminal, enabling quick application.

[0742] For example, if a user enters "I'm thinking of changing jobs to pursue a marketing position," the server analyzes that information, considers relevant skills and experience, and recommends marketing-specific career paths and educational resources. Furthermore, by providing a list of the latest job postings in the marketing field, users can quickly access and apply for suitable positions.

[0743] An example of a prompt message would be, "I am considering a career change to pursue a marketing position. Given my current skill set and experience, what career paths are possible for me, and what should I study?" This collaborative operation across the entire system allows users to effectively manage their careers and navigate the path to their desired profession.

[0744] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0745] Step 1:

[0746] Users input basic data about their personality, interests, experiences, and skills using their own devices. This data is converted into a structured format such as JSON and prepared to be sent to the server. During this preparation stage, the device checks the integrity of the data and verifies that the entered information is valid.

[0747] Step 2:

[0748] The server analyzes the data received from the terminal. AI technology and machine learning algorithms are used for the analysis. User data, as input, is compared with a database of similar historical profiles and market trends to derive suitable occupations and career paths. As output, appropriate career paths are provided, and this information is sent to the user's terminal.

[0749] Step 3:

[0750] The server retrieves labor market information from an external database and integrates it with the analysis results. This external market information includes industry trends and job postings. In this step, the server considers the market data as input, makes appropriate adjustments to the user's career plan, and generates a learning plan. The learning plan is sent to the user's terminal, presenting a roadmap for specific skill development.

[0751] Step 4:

[0752] The server collects information from external educational resources and builds a learning plan tailored to the user's career goals. This step includes a process of extracting information on appropriate online courses and learning materials based on the entered user data. The learning plan clearly outlines the steps necessary for the user's skill improvement, and progress can be monitored on the device.

[0753] Step 5:

[0754] The system searches for and matches job postings. The server scans external job databases and filters job postings to match the user's specified preferences and skill set. Based on the user's preferences, the system selects the most suitable jobs, and these postings are displayed as a list on the user's terminal. This list includes application links, allowing the user to apply directly.

[0755] Step 6:

[0756] Users utilize information provided by their devices to advance their career development. Based on suggested career paths and learning plans, they acquire skills aligned with their goals and apply for jobs. This step supports the entire process from the user's learning to the evaluation of their progress.

[0757] Each processing step involves the server, terminal, and user working together to create a system that comprehensively supports users in designing their career paths.

[0758] (Application Example 1)

[0759] 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".

[0760] Currently, it is a challenging task for individual users to effectively acquire information about career development and improve their skills in daily life. In particular, finding the optimal occupation and career path based on one's own characteristics and creating and executing a learning plan accordingly requires a great deal of manual work. Furthermore, searching for job postings and obtaining application information must be done individually, which is time-consuming and laborious. Therefore, there is a need for consistent support and automated services to solve these problems.

[0761] 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.

[0762] In this invention, the server includes means for analyzing data on the user's characteristics, interests, experience, and skills acquired from an information processing device, means for analyzing industrial market data imported from an external database, and means for acquiring information in cooperation with home automation equipment and enabling interaction with the user. As a result, the user not only automatically receives individually optimized occupations and career plans, but also receives continuous feedback and progress management through interaction via home automation equipment.

[0763] An "information processing device" is an electronic device that has the ability to receive, process, and transmit digital data, and is used to manage information related to the user.

[0764] "Characteristics" refer to attributes related to a user's personality and behavior, and are the basic information that forms the basis of their individual profile.

[0765] "Interests" refer to the fields and themes that users are particularly interested in and passionate about, and are factors that determine the direction of their career development.

[0766] "Experience" refers to the achievements and knowledge gained through past work and activities, and is an important factor that influences future career choices.

[0767] "Skills" refer to the knowledge and abilities required to perform specific tasks or duties, and are indicators used to measure professional competence.

[0768] "Industrial market data" refers to aggregated external information related to economic activity, such as industry trends and employment conditions, and is used for career recommendations through analysis.

[0769] "Home automation devices" refer to digital devices used for information sharing and automated tasks within a home environment, enabling interaction with the user.

[0770] "Analysis means" refers to technical methods for analyzing data about users using information processing equipment to evaluate vocational aptitude and abilities.

[0771] "Analysis means" refers to the processing steps involved in handling data acquired from external sources and generating information that is useful to the user.

[0772] "Dialogue methods" refer to technologies that enable communication between users and systems, and are necessary to provide continuous support.

[0773] The system for carrying out this invention is constructed using an information processing device, a home automation device, and an external database. The server first acquires data on the user's characteristics, interests, experience, and skills through the information processing device. This data is processed by an analysis engine on the server, which generates the most suitable occupation and career path for the user.

[0774] Furthermore, the server retrieves industry market data from an external database and supplements the analysis results. Based on this information, it identifies the skills the user needs and proposes an optimal learning plan and external educational resources. The home automation device presents the user with acquired information and feedback in real time through interaction. This enables the user to efficiently improve their skills in their daily life.

[0775] Home automation devices also search for employment opportunities based on the user's preferences and provide matching job postings. Users can use this information to quickly proceed with the application process. A specific example of use is a user considering a career change taking a career aptitude test and acquiring new skills through recommended learning courses.

[0776] An example of a prompt using a generative AI model is, "What is the best career path and necessary skills to leverage your current experience and move into a new field?" Based on this prompt, the system provides a specific career development plan tailored to the user.

[0777] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0778] Step 1:

[0779] The server receives data from the information processing device regarding the user's characteristics, interests, experience, and skills. This data includes the user's past work history, educational background, and personality test results. Using this as initial input data, the analysis engine begins processing.

[0780] Step 2:

[0781] The server analyzes the received user data using machine learning algorithms. During the data analysis process, clustering and classification techniques are used to generate user profiles based on their characteristics. This results in the output of suitable occupational categories and career paths for each user.

[0782] Step 3:

[0783] The server retrieves industry market data from an external database. This data includes the latest market trends, in-demand skills, and salary information. The server integrates this data with analysis results to generate job and career information optimized for the user.

[0784] Step 4:

[0785] The server presents this generated occupation and career information through home automation devices. The information presented includes learning plans based on the skill sets the user desires and market popularity. The home automation devices interact with the user and accumulate feedback.

[0786] Step 5:

[0787] Based on the information presented, the user sets their own career goals. The server identifies the necessary skills based on these new goals and suggests external educational resources (e.g., online courses and learning materials). This resource information is presented to the user and incorporated into their learning plan.

[0788] Step 6:

[0789] Based on the user's specified preferences, the server searches an external database for job postings and lists suitable employment opportunities. These listed job postings are then provided to the user via a home automation device, along with an application interface.

[0790] Step 7:

[0791] The server and home automation devices work together to collect user feedback and apply that feedback to improve future career development and job search services. This will enable more personalized information and support for users.

[0792] 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.

[0793] This invention combines an emotion engine with an information processing system that supports users' career development, thereby enabling personalized support that takes into account the user's emotions. This system uses an information processing device to analyze data on the user's personality, interests, experience, and skills, and further analyzes labor market data obtained from an external database to suggest suitable occupations and career paths for the user.

[0794] The server receives text or voice data entered by the user on the device and sends it to the emotion engine. This emotion engine uses natural language processing technology to analyze the user's emotions in real time. For example, if the emotion engine determines that the user is stressed or unmotivated, the system takes this into account and adjusts the career plan, providing advice that includes more encouragement and support.

[0795] Furthermore, the analysis results of this emotion engine are also considered when proposing learning plans. The server analyzes the user's emotional state and adjusts learning resources and progress schedules based on that analysis, thereby reducing the user's burden and supporting efficient and effective skill development. In this way, the system is able to understand the user's overall psychological state and propose a flexible learning plan based on that understanding.

[0796] For example, when a user begins a learning plan to pursue a marketing career, the system uses an emotion engine to initially confirm that the user is highly motivated. The server then sets positive learning goals and tracks progress in detail. However, if a decline in motivation is detected along the way, the server adjusts the learning goals based on the emotion engine's assessment and proposes a revised plan at a less stressful pace for the user. It can also provide messages to boost the user's motivation and offer encouraging topics related to skill acquisition.

[0797] This system allows users to develop a personalized career and improve their skills while reducing emotional burden.

[0798] The following describes the processing flow.

[0799] Step 1:

[0800] Users input information about their personality, interests, experiences, and skills using their devices. They can also input their mood and feelings for the day via voice or text as needed.

[0801] Step 2:

[0802] The terminal sends the entered data and voice / text information to the server.

[0803] Step 3:

[0804] The server passes the user's data to the analysis engine, and the analysis begins. Information about personality, interests, experience, and skills is analyzed based on their respective profiles.

[0805] Step 4:

[0806] The server uses an emotion engine to analyze the user's emotional state from received audio or text data. Natural language processing is employed, and emotional indicators are identified as numerical values ​​or categories.

[0807] Step 5:

[0808] The server generates the optimal occupation and career path for the user based on the analysis results. Occupational suggestions are provided using an approach tailored to the user's emotional state.

[0809] Step 6:

[0810] The server takes into account the emotional state determined by the emotion engine and adjusts the tone of messages and suggestions to the user as needed.

[0811] Step 7:

[0812] The device receives carrier suggestions and messages from the server and displays them to the user.

[0813] Step 8:

[0814] The user inputs their career goals and desired skill set from their device and sends it to the server.

[0815] Step 9:

[0816] The server identifies the skills required by the user based on their professional goals. This process includes a gap analysis between the current skill level and market needs.

[0817] Step 10:

[0818] The server takes into account the analysis results from the emotion engine and customizes and proposes a learning plan in a way that reduces the user's psychological burden.

[0819] Step 11:

[0820] The device displays the generated learning plan to the user and provides a function to continuously track their progress.

[0821] Step 12:

[0822] The server periodically updates job data and filters job postings in real time to match the user's desired conditions.

[0823] Step 13:

[0824] The terminal displays job postings received from the server to the user and provides a link to apply.

[0825] In this way, the system comprehensively supports career development while taking into account the user's emotional state.

[0826] (Example 2)

[0827] 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".

[0828] In today's professional environment, there is a demand for prompt and appropriate job and career path suggestions tailored to individual clients. However, traditional methods often fail to consider the individual emotional state of clients, resulting in proposed career plans that are not always suitable for their psychological condition. This can lead to decreased motivation and insufficient results in skill development and career choices.

[0829] 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.

[0830] In this invention, the server includes means for interpreting information about the user's characteristics, interests, experiences, and abilities; means for analyzing employment market information collected from external sources; and means for analyzing the user's emotional state using an emotion engine and adjusting career paths based on that analysis. This makes it possible to propose personalized, emotion-responsive occupational and career plans to the user.

[0831] An "information processing system" is a device that collects and processes user characteristics and external information to perform data analysis and make suggestions.

[0832] "Information sources" refer to external databases or data feeds that provide data on the employment market.

[0833] "Characteristics" refer to the individual features that make up a user's personality and behavioral patterns.

[0834] "Interest" refers to the things that users are interested in or concerned with.

[0835] "Experience" is the accumulation of things that a user has learned and experienced in the past.

[0836] "Ability" refers to the technical or specialized skills and knowledge that the user possesses.

[0837] The "emotion engine" is a program based on natural language processing technology that analyzes user input data and evaluates their emotional state.

[0838] A "career path" refers to a plan that outlines the occupations a user can pursue and the direction of their career development.

[0839] "Personalized advice" refers to advice provided based on the user's unique circumstances and feelings.

[0840] To implement this invention, an information processing system equipped with an emotion engine is required. The server first receives text or voice data from the user via a terminal. This data includes the user's characteristics, interests, experiences, abilities, and current emotional state. Next, the server passes the received data to the emotion engine, which analyzes the user's emotional state in real time. This analysis utilizes natural language processing technology, such as using libraries like the Google Natural Language API.

[0841] The server analyzes the latest job market information obtained from external sources based on the analysis results. This analysis utilizes Apache Hadoop and other commonly used big data processing platforms. This generates suitable occupations and career paths for the user and provides advice. During this process, a career plan generated using a generative AI model is presented to the user.

[0842] For example, if a user enters "I'm interested in digital marketing" into their device, the server sends this information to the emotion engine and data analysis engine to develop an optimal career plan. If high stress levels are detected in the user, the server provides a flexible learning plan to alleviate that pressure. An example of a prompt would be, "Please create a learning plan for a marketing career. Include content that reduces user stress and increases motivation."

[0843] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0844] Step 1:

[0845] Users input text or voice data about their occupation and career through their device. This input data includes the user's characteristics, interests, experience, and abilities. The device then transmits this data to the server.

[0846] Step 2:

[0847] The server sends the received data to the emotion engine. The emotion engine uses natural language processing technology to analyze the user's input data in real time and evaluate their emotional state. Specifically, it determines the user's stress level and motivation based on emotional indicators extracted from the text. It generates data indicating the emotional state as output.

[0848] Step 3:

[0849] The server analyzes the analyzed emotional state data and the user's characteristics, interests, experiences, and abilities, along with the latest job market information obtained from external sources. Specifically, it uses big data processing tools to identify the most suitable occupations and career paths for the user. This analysis generates a list of candidate occupations and career paths to suggest to the user.

[0850] Step 4:

[0851] The server creates a career plan optimized for the user based on the generated list of candidate career paths and the user's emotional state. A generative AI model is used to generate a customized plan tailored to the user's needs and emotional state. The output includes a career plan with specific job suggestions and a learning plan.

[0852] Step 5:

[0853] The server sends the final generated career plan to the terminal and presents it to the user. Based on the information presented, the user can decide on future career choices and actions for skill development. If feedback or further suggestions are needed, the system takes this into account and adjusts the plan accordingly.

[0854] (Application Example 2)

[0855] 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".

[0856] Traditional career development support systems provided job suggestions based on users' personality and skill data, but they failed to consider changes in users' emotions and motivation, resulting in insufficient personalized support. Furthermore, they were unable to dynamically adjust learning plans based on users' daily emotions, making efficient skill improvement difficult.

[0857] 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.

[0858] In this invention, the server includes means for analyzing data on the user's personality, interests, experiences, and skills acquired from an information processing device; means for analyzing labor market data imported from an external database; and means for analyzing the user's emotional state in real time using an emotion analysis engine and making adjustments to the generated occupation and career path based on the emotional information. This enables the provision of personalized career plans tailored to each user's emotional state and the dynamic adjustment of effective learning plans.

[0859] An "information processing device" is a system for acquiring and analyzing data related to a user's personality, interests, experiences, and skills.

[0860] An "external database" is a data storage system that accumulates information about the labor market and allows this information to be imported for analysis.

[0861] An "emotion analysis engine" is an analysis system equipped with technology that determines the emotional state of a user in real time based on text and voice data acquired from them.

[0862] A "career path" is a plan that outlines suitable occupations for the user and the career development process leading up to them.

[0863] A "learning plan" is a plan that includes a procedure and resource allocation aimed at acquiring the skills necessary to achieve the occupational goals set by the user.

[0864] "Adjustment" refers to the process of dynamically modifying plans and proposals based on the user's current emotional state and progress.

[0865] "Job postings" refer to data on employment opportunities obtained from the labor market, including details of jobs that users can apply for.

[0866] The system for implementing this invention aims to provide users with career development support optimized for their needs. This system functions as an information processing device, an external database, and an emotion analysis engine.

[0867] The server retrieves data on the user's personality, interests, experience, and skills from an information processing device. By analyzing this data, it gains a detailed understanding of the user's characteristics. In addition, the server imports labor market data from an external database and analyzes it to generate suitable occupations and career paths for the user.

[0868] Furthermore, the emotion analysis engine processes the user's input text and voice data in real time to determine their emotional state. Specifically, it uses natural language processing technology to analyze text and capture changes in emotions and motivation. For example, it can utilize natural language processing libraries using Python (such as NLTK or spaCy).

[0869] Based on the results of emotion analysis, the server dynamically adjusts the career path and learning plan. This enables flexible support tailored to the user's emotional state and progress. Furthermore, hardware devices equipped with microphones and speakers can be used, allowing for voice data input and interaction.

[0870] As a concrete example, if a user reports work-related stress on a given day, the system recognizes that emotion through emotion analysis and proposes new relaxing activities in the learning plan. An example of a related generative AI model prompt is as follows:

[0871] "When a user is feeling stressed, what suggestions do you offer? Please include relaxation methods as well."

[0872] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0873] Step 1:

[0874] The user inputs text or voice data into the device. The device receives this data and converts it into digital data. This data is then sent to the server as input.

[0875] Step 2:

[0876] The server processes the received digital data using an information processing device. Specifically, it utilizes natural language processing technology to analyze the user's personality, interests, experiences, and skills, and generates a personality profile. This profile is then output.

[0877] Step 3:

[0878] The server accesses an external database to retrieve current labor market data. This data includes various information about occupations. The information retrieved from the database is analyzed as input, and the results of the labor market trend analysis are output.

[0879] Step 4:

[0880] The server integrates the generated personality profile with analyzed labor market information. Based on this, it generates suitable occupations and career paths for the user. Personalized career suggestions are output using the generated AI model.

[0881] Step 5:

[0882] The received text or audio data is sent to the sentiment analysis engine. The sentiment analysis engine uses natural language processing to analyze the data and determine the user's real-time emotional state. The emotional information obtained during this process is then output.

[0883] Step 6:

[0884] The server dynamically adjusts the generated carrier path based on emotional information. By incorporating emotional support elements, it redesigns the carrier plan to better suit the user. This redesigned plan is then output.

[0885] Step 7:

[0886] The system presents users with redesigned career paths and learning plans via their devices. Furthermore, it offers suggestions for relaxation and motivation enhancement. In this process, it utilizes prompts from a generated AI model to ensure optimal communication.

[0887] 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.

[0888] 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.

[0889] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0890] 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.

[0891] 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.

[0892] 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.

[0893] 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.

[0894] 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.

[0895] 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."

[0896] 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.

[0897] 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.

[0898] 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.

[0899] 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.

[0900] 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.

[0901] 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.

[0902] 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.

[0903] 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.

[0904] 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.

[0905] 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.

[0906] 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.

[0907] 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.

[0908] The following is further disclosed regarding the embodiments described above.

[0909] (Claim 1)

[0910] A means for analyzing data on a user's personality, interests, experience, and skills obtained from an information processing device,

[0911] Methods for analyzing labor market data imported from external databases,

[0912] A means for generating suitable occupations and career paths for users based on the aforementioned analysis and results,

[0913] A means of presenting generated occupations and career paths to users,

[0914] A system that includes this.

[0915] (Claim 2)

[0916] A means of identifying the skills necessary for the occupational goals set by the user,

[0917] A means of proposing learning plans and resources based on identified skills,

[0918] A means of tracking and evaluating the learning progress of users,

[0919] The system according to claim 1, including the following:

[0920] (Claim 3)

[0921] A means of searching for job postings based on the user's desired conditions,

[0922] A method for selecting suitable job postings from search results,

[0923] A means of presenting selected job postings to users and providing links to apply,

[0924] The system according to claim 1, including the following:

[0925] "Example 1"

[0926] (Claim 1)

[0927] A means of analyzing data on characteristics obtained from users,

[0928] Methods for analyzing external labor market information,

[0929] A means for generating a suitable occupational path based on the aforementioned analysis and results,

[0930] Means for presenting generated career paths,

[0931] A means of obtaining information from external educational resources and generating a learning plan,

[0932] A system that includes this.

[0933] (Claim 2)

[0934] A means of identifying the skills required to achieve the set objectives,

[0935] Means for proposing a plan based on identified skills,

[0936] Means for tracking learning progress,

[0937] The system according to claim 1, including the following:

[0938] (Claim 3)

[0939] A means of searching for job postings based on desired conditions,

[0940] Methods for selecting suitable job openings,

[0941] A means of presenting selected information and providing a link to apply,

[0942] The system according to claim 1, including the following:

[0943] "Application Example 1"

[0944] (Claim 1)

[0945] A means for analyzing data on user characteristics, interests, experiences, and skills acquired from an information processing device,

[0946] A means of analyzing industrial market data imported from an external database,

[0947] A means for generating suitable occupations and career paths for users based on the aforementioned analysis and results,

[0948] A means of presenting generated occupations and career paths to users,

[0949] A means of acquiring information in conjunction with home automation devices and enabling interaction with users,

[0950] A system that includes this.

[0951] (Claim 2)

[0952] A means of identifying the skills necessary for the occupational goals set by the user,

[0953] A means of proposing learning plans and external educational resources based on identified skills,

[0954] A means of tracking and evaluating the learning progress of users,

[0955] A means of providing feedback to users through home automation equipment,

[0956] The system according to claim 1, including the following:

[0957] (Claim 3)

[0958] A means of searching for employment opportunity information based on the user's desired conditions,

[0959] A means of selecting suitable employment opportunities for users from search results,

[0960] A means of presenting selected employment opportunity information to users and providing an interface that allows them to apply,

[0961] A means of providing users with application-related guidance through home automation equipment,

[0962] The system according to claim 1, including the following:

[0963] "Example 2 of combining an emotion engine"

[0964] (Claim 1)

[0965] Means for interpreting information about the user's characteristics, interests, experiences, and abilities obtained from an information processing system,

[0966] Methods for analyzing employment market information collected from external sources,

[0967] Based on the above interpretation and analysis results, means for creating occupations and career paths suitable for the user,

[0968] A means of presenting the created occupations and career paths to the user,

[0969] A means of incorporating an emotion engine to analyze the emotional state of users,

[0970] A means of adjusting occupational and career paths and providing individualized advice based on emotional states,

[0971] A system that includes this.

[0972] (Claim 2)

[0973] A means of identifying the necessary skills that align with the occupational goals set by the user,

[0974] A means of proposing learning plans and materials based on identified abilities,

[0975] A means of monitoring and determining the learning progress of users,

[0976] A means of adjusting the learning plan based on the analysis results from the emotion engine,

[0977] The system according to claim 1, including the following:

[0978] (Claim 3)

[0979] A means of searching for occupational information according to the user's desired conditions,

[0980] A method for selecting the most suitable occupation for the user from the search results,

[0981] A means of presenting selected job information to users and providing links that allow them to apply,

[0982] The system according to claim 1, including the following:

[0983] "Application example 2 when combining with an emotional engine"

[0984] (Claim 1)

[0985] A means for analyzing data on a user's personality, interests, experience, and skills obtained from an information processing device,

[0986] Methods for analyzing labor market data imported from external databases,

[0987] A means for generating suitable occupations and career paths for users based on the aforementioned analysis and results,

[0988] A means of analyzing the user's emotional state in real time using an emotion analysis engine and making adjustments to the generated occupation and career path based on emotional information,

[0989] A means of presenting adjusted occupations and career paths to users,

[0990] A system that includes this.

[0991] (Claim 2)

[0992] A means of identifying the skills necessary for the occupational goals set by the user,

[0993] Based on identified skills, a means of proposing learning plans and resources, and performing dynamic adjustments based on emotional state,

[0994] A method for tracking users' learning progress and evaluating it using sentiment analysis,

[0995] The system according to claim 1, including the following:

[0996] (Claim 3)

[0997] A method for searching job postings based on the user's desired conditions and performing a suitability assessment that takes emotions into consideration,

[0998] A method for selecting suitable job postings from search results,

[0999] A means of presenting selected job postings to users and providing links to apply,

[1000] The system according to claim 1, including the following: [Explanation of Symbols]

[1001] 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. A means for analyzing data on user characteristics, interests, experiences, and skills acquired from an information processing device, A means of analyzing industrial market data imported from an external database, A means for generating suitable occupations and career paths for users based on the aforementioned analysis and results, A means of presenting generated occupations and career paths to users, A means of acquiring information in conjunction with home automation devices and enabling interaction with users, A system that includes this.

2. A means of identifying the skills necessary for the occupational goals set by the user, A means of proposing learning plans and external educational resources based on identified skills, A means of tracking and evaluating the learning progress of users, A means of providing feedback to users through home automation equipment, The system according to claim 1, including the following:

3. A means of searching for employment opportunity information based on the user's desired conditions, A means of selecting suitable employment opportunities for users from search results, A means of presenting selected employment opportunity information to users and providing an interface that allows them to apply, A means of providing users with application-related guidance through home automation equipment, The system according to claim 1, including the following:

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