System

Abstract

A system is provided.SOLUTION: A system comprising: means for a user to input skills, educational levels, background, and goals; means for transmitting the input information to a server; means for the server to store the received information in a database; means for analyzing the stored information; means for generating an optimal career plan and learning plan; means for transmitting the generated plan to the user; means for the user to confirm the transmitted plan; and means for the server to readjust the plan based on the received feedback.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the 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] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In today's world, new skills and knowledge are constantly required in many industries, including the technology sector, but many workers are unclear about their specific career paths and do not know how to reskill or upskill. In such situations, it is necessary to present optimal career and learning plans tailored to each individual's skills, background, and goals, but this is difficult because it is time-consuming and requires sensitive response to market fluctuations. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides an AI system that allows a user to input their skills, educational level, career history, and goals, and then proposes optimal career and study plans based on the input. The system of the present invention includes the following means.

[0006] The system includes a means for a user to input skills, educational level, career history, and goals, a means for transmitting the input information to a server, a means for the server to store the received information in a database, a means for performing data analysis based on the stored information, a means for generating optimal career and study plans based on the analysis results, a means for transmitting the generated plans to the user's terminal, a means for the user to confirm the transmitted plans, a means for transmitting user feedback to the server, and a means for the server to readjust the plans based on the feedback received.

[0007] This allows users to clearly understand their career path and efficiently proceed with reskilling and upskilling. It also includes a means for collecting market trends and job information and generating users' career and learning plans based on this, allowing for flexible responses to market fluctuations. Furthermore, the system includes a means for users' devices to display plans in a visually easy-to-understand format, enhancing user convenience.

[0008] "User" refers to an individual or company who uses the system to input their skills, educational level, career history, and goals, and receives suggestions for career and learning plans.

[0009] "Skills" refer to the techniques, abilities, and knowledge that a user has acquired.

[0010] "Education level" refers to the highest level of education or educational qualifications a user has achieved.

[0011] "Career" refers to the user's past job, employment history, and work experience.

[0012] "Goals" refer to the career or professional goals that a user wants to achieve in the future.

[0013] "Server" refers to a computer system that receives, stores, analyzes data entered by a user, and returns the results.

[0014] A "database" refers to a collection of data used to store and manage user information, market trends, etc.

[0015] "Data analysis" refers to the analytical work carried out to generate optimal career and study plans based on collected user information and market trends.

[0016] A "career plan" refers to the specific path or steps a user takes to reach their desired career goal.

[0017] "Study Plan" refers to specific learning methods and course suggestions for users to acquire new skills or knowledge.

[0018] "Feedback" refers to the opinions and evaluations provided by the user regarding the plans proposed by the system. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6]FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 1, a 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.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the 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.

[0033] 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] This invention relates to an AI system that proposes optimal career and study plans to help users achieve their career goals. This system generates and presents appropriate plans to users based on their skills, educational level, career history, and goals.

[0041] System configuration

[0042] The system configuration is as follows:

[0043] 1. User Interface

[0044] Users input their skills, education level, background, and goals, which are provided in the form of a website or mobile application.

[0045] 2. Data Transmission

[0046] The user's device sends the entered information to the server. The data is sent using a secure protocol (e.g., HTTPS).

[0047] 3. Data Storage

[0048] The server stores the received information in a database, which efficiently manages user information and allows for rapid data access.

[0049] 4. Data Analysis

[0050] The server uses the stored information to run AI algorithms that generate optimal career and study plans based on the user's skills, education level, background, and goals.

[0051] 5. Plan Generation and Presentation

[0052] The server sends the generated plan to the user's device, where the user can check the plan and learn the specific steps.

[0053] 6. Feedback and Recalibration

[0054] The server receives the feedback provided by the user and readjusts the career and study plans accordingly.

[0055] Explanation of program processing

[0056] The program processing in this system is carried out as follows.

[0057] 1. Entering and submitting information

[0058] The user inputs their skills, educational level, career history, and goals, and sends the information to the server by pressing the send button.

[0059] For example, a user enters and submits information such as "Python programming," "university graduate," "5 years of experience as a software engineer," and "I want to become an AI engineer."

[0060] 2. Receipt and storage of data

[0061] The server receives the information sent by the user and stores the information in a database.

[0062] For example, information about each user is stored in a corresponding table (eg, a skills table, an education table, a career table) in the database.

[0063] 3. Data Analysis

[0064] An AI algorithm on the server retrieves user information from the database and analyzes it.

[0065] For example, if a user's goal is to "become an AI engineer," an AI algorithm will recommend "machine learning" and "data science" as necessary skills.

[0066] 4. Plan Generation

[0067] The server generates optimal career and study plans based on the analysis results of the AI ​​algorithm.

[0068] For example, specific plans such as "take an online data science course" or "start a machine learning project in Python" are generated.

[0069] 5. Presenting the plan

[0070] The server sends the generated plan to the user's terminal, where the user can view the plan.

[0071] For example, a "data science course link" or a "list of practical project ideas" will be displayed on the user's device.

[0072] 6. Receive feedback and readjust

[0073] The user sends feedback about the plan to the server, which then readjusts the career and learning plan based on the feedback.

[0074] For example, if a user submits feedback indicating interest in a particular course, the server generates a new plan accordingly.

[0075] This process effectively enables users to take concrete steps towards their career goals.

[0076] The processing flow will be explained below.

[0077] Program processing flow

[0078] Step 1:

[0079] Users log in to the platform, either by creating an account if they are new users or by entering their login details if they are existing users.

[0080] Step 2:

[0081] Users input their skills, education level, background, and goals, clarifying their current status and future goals.

[0082] Step 3:

[0083] The device sends the entered information to the server. The data is transmitted using a secure protocol (e.g., HTTPS).

[0084] Step 4:

[0085] The server receives the information sent by the users and stores it in a database, organized by user and recorded in the appropriate tables.

[0086] Step 5:

[0087] The server retrieves the stored user information from the database and passes it to the AI ​​algorithm, which analyzes this information and generates the optimal career and study plan for the user.

[0088] Step 6:

[0089] Based on the results of the AI ​​algorithm's analysis, the server generates a specific career and learning plan, such as "take an online data science course and start a machine learning project in Python."

[0090] Step 7:

[0091] The server sends the generated plan to the user's device, where it is encoded in JSON format and received by the device.

[0092] Step 8:

[0093] The user checks the generated plan on their own device, which displays the plan in a visually easy-to-understand format.

[0094] Step 9:

[0095] The user inputs feedback about the proposed plan and sends it to the server. The feedback includes evaluation of the plan and requests for additions.

[0096] Step 10:

[0097] The server receives feedback from the user and adjusts the career and learning plans based on this feedback, generating new plans as needed and sending them back to the user's device.

[0098] This process provides users with concrete steps to effectively advance their careers.

[0099] Example 1

[0100] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0101] Conventional career and learning plan proposal systems have struggled to generate optimal plans based on a user's individual skills and goals. Furthermore, they lacked a mechanism for appropriately reflecting and adjusting user feedback on the generated plans, making it difficult to provide plans that maximize the user's benefits. Furthermore, generating plans that take into account economic trends and job information, and providing displays that are visually easy to understand, were also issues.

[0102] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0103] In this invention, the server includes: means for a user to input their abilities, educational level, work history, and goals; means for transmitting the input data to a computer; means for the computer to store the received data in a data storage device; means for processing the stored data; means for generating an optimal career plan and study plan based on the results of the information processing; means for the user to confirm the transmitted plan; means for the user to transmit the user's opinions to the computer; means for the computer to readjust the plan based on the received opinions; means for collecting economic trends and employment information and generating the user's career plan and study plan based thereon; and means for the user's information processing device to display the plan in a visually easy-to-understand format. This enables the provision of an optimal career and study plan based on the user's individual skills and goals, and also makes it easy to readjust the plan by reflecting the user's feedback. As a result, a plan that is most effective for the user can be provided.

[0104] "Ability" refers to the level of a user's technology and knowledge, including specific skills and specialized knowledge.

[0105] "Educational level" refers to the user's educational background and level of education, including classifications such as junior high school graduate, high school graduate, and university graduate.

[0106] "Work experience" refers to the occupations, industries, positions, etc. that a user has had up to now, including specific years of employment and roles.

[0107] "Goals" refer to the specific objectives and visions that a user wants to achieve in relation to their occupation or career, and include long-term goals and short-term goals.

[0108] "Computer" refers to a central control unit that processes, stores, and analyzes information sent by users, and primarily functions as a server.

[0109] "Data storage device" refers to a device for storing user information received by a computer, including a database or other storage medium.

[0110] "Information processing" refers to a series of processes that analyze and calculate stored data to derive meaningful results, and primarily involves analysis using AI algorithms.

[0111] A "career plan" refers to specific career paths and steps proposed based on the user's career goals, including methods for acquiring necessary skills and education.

[0112] A "learning plan" refers to a specific learning method or course that a user uses to acquire new skills or knowledge, including online courses and hands-on projects.

[0113] "Information processing equipment" refers to a terminal that allows a user to interact with a computer, and primarily includes devices such as smartphones and PCs.

[0114] "Opinions" means feedback or comments provided by users, including information needed to improve or adjust the Plan.

[0115] "Economic trends" refers to current market conditions and overall economic trends, including job information and industry growth forecasts.

[0116] "Employment information" refers to information related to specific job openings and job seekers in the current job market, including employment conditions and required skills.

[0117] "Visually easy to understand" refers to a display format that allows users to intuitively understand the proposed plan, including graphical interfaces and infographics.

[0118] MODE FOR CARRYING OUT THE INVENTION

[0119] This invention relates to a system that proposes optimal career and study plans based on the abilities, educational level, work history, and goals input by a user. This system is realized mainly using a user terminal, a server, a data storage device, and various software components.

[0120] User terminal

[0121] A user terminal is a device that a user uses to access a system and input the necessary information. This mainly includes PCs, smartphones, and tablets. Users input information into a form displayed on the terminal screen.

[0122] For example, enter the following information:

[0123] Skills: Python programming

[0124] Education level: University graduate

[0125] Work Experience: 5 years of experience as a software engineer

[0126] Goal: I want to become an AI engineer

[0127] server

[0128] The server receives the information sent by the user and stores it in a data storage device. The data from the user is transmitted via a secure protocol (e.g., HTTPS). The received data is stored in a database.

[0129] Data Storage Device

[0130] Data storage is a system that organizes user information appropriately and makes it quickly accessible, using a relational database management system (RDBMS) or a NoSQL database.

[0131] Information Processing

[0132] The server retrieves the information stored in the data storage device and analyzes it using AI algorithms. These algorithms utilize generative AI models to recommend skills and learning resources needed to achieve the user's goals. Data analysis software such as Python and R is used on the server.

[0133] for example,

[0134] If a user's goal is to "become an AI engineer," the AI ​​algorithm will determine that skills like "machine learning" and "data science" are required, and will then recommend appropriate online courses and projects.

[0135] Plan Generation

[0136] Based on the analysis results of the AI ​​algorithm, the server generates a career plan and study plan tailored to each user. The plan includes specific steps and is presented in a form that the user can follow.

[0137] For example, specific plans such as "take an online data science course" or "start a machine learning project in Python" are generated.

[0138] Presenting the plan

[0139] The server sends the generated plan to the user's device, where the user can view the plan on their own device. Specifically, the plan displays "Data Science Course Links" and "Practical Project Idea List," allowing the user to access these resources.

[0140] Receive feedback and readjust

[0141] The user provides feedback on the proposed plan, for example, by inputting specific opinions such as "I'm interested in this course" or "This step is too difficult." The server receives this feedback and readjusts the plan using an AI algorithm. The adjusted plan is then sent back to the user's device, where the user can review the new proposal.

[0142] Example prompt

[0143] As a concrete example, the following prompts can be provided to a generative AI model:

[0144] "If a user sets a goal of 'I want to become an AI engineer,' please provide them with the necessary skills and a recommended learning plan."

[0145] "How do we generate the optimal learning plan for a user with Python programming skills, a college degree, and five years of software engineering experience?"

[0146] By implementing this invention, users are empowered to take concrete and effective steps towards their career goals.

[0147] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0148] Step 1:

[0149] User enters information and submits

[0150] The user enters the following information into a form on their device: ability (e.g., Python programming), level of education (e.g., university graduate), work experience (e.g., 5 years of experience as a software engineer), and goal (e.g., want to become an AI engineer). After entering the information, they press the "Submit" button, and this information is sent to the server using HTTPS.

[0151] Input: User skills, education level, work history, goals

[0152] Output: User information sent to the server

[0153] Step 2:

[0154] The server receives and stores the data

[0155] The server receives the data sent by the user and stores it in a data storage device. In the database, skill information is stored in a skill table, education level in an education table, and work history in a work history table.

[0156] Input: User information sent to the server

[0157] Output: User information stored in the database

[0158] Step 3:

[0159] The server analyzes the data

[0160] The server retrieves user information stored in the database and analyzes it using an AI algorithm. The AI ​​algorithm then uses a generative AI model to recommend skills and learning resources necessary to achieve the user's goals. For example, if the goal is to "become an AI engineer," the analysis results would include "machine learning" and "data science."

[0161] Input: User information stored in the database

[0162] Output: Recommendations for optimal skills and learning resources

[0163] Step 4:

[0164] The server generates a plan

[0165] Based on the results of the AI ​​algorithm's analysis, the server generates a personalized career and learning plan for each user, with specific steps such as "take an online data science course" or "start a machine learning project in Python."

[0166] Input: Recommendations for optimal skills and learning resources

[0167] Output: Generated career and study plans

[0168] Step 5:

[0169] The server presents the plan to the user

[0170] The server sends the generated plan to the user's device, where the user can view it and see specific links and steps in a visually understandable format. For example, "Data Science Course Links" and "Practical Project Idea List" are displayed.

[0171] Input: Generated career and study plans

[0172] Output: The plan displayed on the user's device

[0173] Step 6:

[0174] Users provide feedback and readjust

[0175] The user provides feedback on the presented plan, such as "I'm interested in this course" or "This step is too difficult." The server receives this feedback and readjusts the plan using an AI algorithm. The adjusted plan is then sent back to the user's device.

[0176] Input: User feedback

[0177] Output: Realigned career and study plans

[0178] (Application example 1)

[0179] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0180] Currently, there are systems that suggest career and learning plans, but there is a lack of systems that support payment management and fund tracking for related learning courses and services. Furthermore, the ability to adjust plans based on user feedback is insufficient, making it difficult to flexibly respond to user needs.

[0181] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0182] In this invention, the server includes: a means for a user to input skills, educational level, career history, and goals; a means for transmitting the input information to the server; a means for performing data analysis based on the stored information; a means for generating an optimal career plan and learning plan based on the analysis results; a means for managing payments for learning courses and services based on the proposed plan; and a means for providing and tracking the use of funds for achieving the career plan. This allows users to centrally manage payments for learning courses and services to implement their optimal career plan and track the use of funds. Furthermore, by readjusting the plan based on user feedback, the plan can be flexibly changed to meet needs.

[0183] "User" refers to any individual or legal entity that uses the System.

[0184] "Skills" refer to the abilities and knowledge required to perform a particular task or activity.

[0185] "Education level" refers to the educational background and learning progress of the user at an educational institution.

[0186] A "career history" is a record of a user's work history and professional experience.

[0187] "Goals" refer to the specific career or learning goals that a user is trying to achieve.

[0188] "Server" refers to an information processing device that receives and stores data from users and processes that data.

[0189] "Database" means the data structures and software systems used to manage and store User information.

[0190] "Data analysis" refers to the analytical process that the system uses to generate optimal career and study plans based on the input user information.

[0191] "Career plan" refers to the plan and specific steps a user takes to reach the career or job they are aiming for.

[0192] "Study Plan" means the learning plan and specific courses that a User takes to acquire the necessary skills toward their career goals.

[0193] "Payment" refers to the act of a user paying for a learning course or service provided.

[0194] "Funding Tracking" refers to the management and recording of funds a user has invested to achieve their career goals.

[0195] "Feedback" refers to the opinions and evaluations provided by users regarding proposed plans.

[0196] "Readjustment" refers to modifying or changing existing career or study plans based on feedback received from users.

[0197] Overall system configuration

[0198] This invention is an AI system for supporting users in achieving their career goals, and in particular has a payment management function related to career and learning plan proposals. The system includes the following main components:

[0199] User Interface

[0200] Data transmission

[0201] Data Storage

[0202] Data analysis

[0203] Plan generation and presentation

[0204] Feedback and Recalibration

[0205] Payment Management

[0206] Funds Tracking

[0207] User Interface

[0208] Users are provided with an interface to input their skills, education level, background, and goals, which can be entered through a website or mobile application.

[0209] Data Transmission and Storage

[0210] The information entered by the user is sent to the server using a secure protocol (e.g. HTTPS), and the server stores the received information in a database for efficient management.

[0211] Data analysis and plan generation

[0212] The server runs AI algorithms based on the stored information to generate optimal career and learning plans based on the user's skills, education level, background, and goals. The AI ​​models used include the Logistic Regression model.

[0213] Plan presentation and feedback

[0214] The generated plan is sent to the user's device for review, and the user can provide feedback on the plan, which the server then uses to adjust the plan.

[0215] Payment Management

[0216] Payment for the proposed course or service is managed within the system, and payment is completed by entering payment information.

[0217] Funds Tracking

[0218] It also provides a tracking function for the use of funds invested in achieving career plans, allowing users to manage their funds efficiently.

[0219] Adding specific examples to the description

[0220] For example, a user enters the information "Python programming", "college graduate", "5 years of experience as a software engineer", and "I want to become an AI engineer", and sends the following prompt to the server:

[0221] Skills: Python programming

[0222] Education level: University graduate

[0223] Experience: 5 years of experience as a software engineer

[0224] Goal: I want to become an AI engineer

[0225] This information is stored in a database, and the AI ​​model performs the necessary analysis to generate a specific career plan, such as "take an online data science course" or "start a machine learning project in Python." This plan is then presented to the user, who can then make course payments and manage their finances centrally based on the proposal.

[0226] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0227] Step 1:

[0228] Users enter their skills, education level, background, and goals.

[0229] The input information could be, for example, "Python programming," "university graduate," "5 years of experience as a software engineer," or "I want to become an AI engineer." This information is provided through a user interface (website or mobile application).

[0230] Step 2:

[0231] The user's terminal transmits the input information to the server.

[0232] This uses a secure protocol such as HTTPS.

[0233] Input data is sent and the server receives the data.

[0234] Step 3:

[0235] The server stores the received information in a database.

[0236] The data stored includes skill information, education level, career history, and goals, making it easier to manage user information on the database.

[0237] Step 4:

[0238] An AI algorithm on the server retrieves user information from the database and performs data analysis.

[0239] Specifically, it uses AI models (e.g., logistic regression) to analyze the user's skills and goals, which then triggers the creation of a career and learning plan tailored to the user.

[0240] Step 5:

[0241] The server generates a career plan and a study plan based on the analysis results.

[0242] For example, the generated plan might include "Take an online data science course" or "Start a machine learning project in Python," giving users a clear understanding of the steps involved.

[0243] Step 6:

[0244] The generated plan is sent to the user's terminal.

[0245] The user's device displays this received information in a visually easy-to-understand format, such as course links or a list of project ideas on the user interface.

[0246] Step 7:

[0247] The user reviews the generated plan and provides feedback.

[0248] The feedback includes evaluation of the plan and suggestions for improvement, etc. The feedback is sent back to the server.

[0249] Step 8:

[0250] The server readjusts the plan based on the feedback it receives.

[0251] A new, optimized plan is generated based on the user's opinions, allowing for flexible changes to the plan according to the user's needs.

[0252] Step 9:

[0253] The server manages payments for learning courses and services based on the proposed plan.

[0254] Once the user enters their payment information, the payment is completed and stored in a database, facilitating access to related courses and services.

[0255] Step 10:

[0256] The server provides usage and tracking of funds invested in achieving career plans.

[0257] Users can view the progress and usage history of their funds, which allows them to manage their funds according to plan.

[0258] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0259] This invention relates to an AI system that proposes optimal career and study plans to help users achieve their career goals. The system generates appropriate plans based on the user's skills, educational level, career history, and goals, and also has the ability to recognize the user's emotions and adjust the plans accordingly.

[0260] System configuration

[0261] The system configuration is as follows:

[0262] 1. User Interface

[0263] Users input their skills, education level, background, and goals, which are provided in the form of a website or mobile application.

[0264] 2. Data Transmission

[0265] The user's device sends the entered information to the server. The data is transmitted using a secure protocol (e.g., HTTPS).

[0266] 3. Data Storage

[0267] The server stores the received information in a database, which efficiently manages user information and allows for rapid data access.

[0268] 4. Data Analysis

[0269] The server uses the stored information to run AI algorithms that generate optimal career and study plans based on the user's skills, education level, background, and goals.

[0270] 5. Emotion Engine

[0271] It is equipped with an emotion engine that recognizes the user's emotions. The emotion engine analyzes emotions from the user's input and dialogue history.

[0272] 6. Plan generation and consideration of emotional feedback

[0273] The server takes into account the analysis results of the AI ​​algorithm and feedback from the emotion engine to generate the optimal career and study plans for the user.

[0274] For example, if a user is feeling stressed, suggestions for relaxing study methods can be included.

[0275] 7. Plan Presentation

[0276] The server sends the generated plan to the user's device, where the user can view the plan and learn the specific steps.

[0277] 8. Feedback and Recalibration

[0278] The server receives the feedback and emotional data provided by the user and readjusts the career and learning plans accordingly.

[0279] Explanation of program processing

[0280] The program processing in this system is carried out as follows.

[0281] 1. Entering and submitting information

[0282] Users input their skills, education level, background, goals, as well as emotional input (e.g., "I'm feeling stressed").

[0283] This information is sent to the server by pressing the send button.

[0284] 2. Receipt and storage of data

[0285] The server receives the information sent by the user and stores it in a database.

[0286] The information is organized for each user and recorded in the appropriate tables.

[0287] 3. Data Analysis

[0288] An AI algorithm on the server retrieves user information from the database and analyzes it.

[0289] For example, if a user's goal is to "become an AI engineer," the system will recommend "machine learning" and "data science" as necessary skills.

[0290] 4. Emotion Data Analysis

[0291] The server's emotion engine analyzes the user's emotion data and determines the user's current emotional state.

[0292] 5. Plan Generation

[0293] The server generates optimal career and study plans based on the analysis results of the AI ​​algorithm and feedback from the emotion engine.

[0294] For example, specific plans such as "take an online data science course" or "start a machine learning project in Python" are generated.

[0295] 6. Presenting the plan

[0296] The server sends the generated plan to the user's device, where it is encoded in JSON format and received by the device.

[0297] 7. User Confirms Plan

[0298] The user checks the generated plan on their own device, which displays the plan in a visually easy-to-understand format.

[0299] 8. Receive feedback and readjust

[0300] The user inputs feedback about the plan and sends it to the server. The feedback includes evaluation of the plan and requests for additions.

[0301] The server receives feedback and emotional data from users and readjusts their career and learning plans based on this.

[0302] This series of processes allows users to obtain concrete steps to effectively advance their careers. In addition, the emotion engine reduces the user's psychological burden and provides more appropriate suggestions.

[0303] The processing flow will be explained below.

[0304] Program processing flow

[0305] Step 1:

[0306] Users log in to the platform, either by creating an account if they are new users or by entering their login details if they are existing users.

[0307] Step 2:

[0308] Users input their skills, education level, career history, goals, and current emotional state. For example, they input "Python programming" as a skill, "university graduate" as an education level, "5 years of experience as a software engineer" as a career history, "I want to become an AI engineer" as a goal, and "I feel stressed" as an emotional state.

[0309] Step 3:

[0310] The device sends the entered information to the server. The data is transmitted using a secure protocol (e.g., HTTPS).

[0311] Step 4:

[0312] The server receives the information sent by the users and stores it in a database, organized by user and recorded in the appropriate tables.

[0313] Step 5:

[0314] The server retrieves the stored user information from the database and passes it to the AI ​​algorithm, which analyzes this information and generates the optimal career and study plan for the user.

[0315] Step 6:

[0316] The server's emotion engine analyzes the user's emotion data. For example, if the user is "feeling stressed," the emotion engine analyzes the data and understands the user's psychological state.

[0317] Step 7:

[0318] Based on the analysis results of the AI ​​algorithm and feedback from the emotion engine, the server generates specific career and learning plans, such as "take an online data science course and start a machine learning project in Python," as well as "suggestions for relaxing study methods."

[0319] Step 8:

[0320] The server sends the generated plan to the user's device, where it is encoded in JSON format and received by the device.

[0321] Step 9:

[0322] The user can then view the generated plan on their device. The device displays the plan in a visually easy-to-understand format. For example, the user's device displays a "Data Science course link" and a "List of ideas for practical projects."

[0323] Step 10:

[0324] The user inputs feedback about the presented plan and sends it to the server. The feedback includes an evaluation of the plan and requests for additions. For example, the user can send feedback such as "The course is too difficult."

[0325] Step 11:

[0326] The server receives feedback from the user and, together with the emotion engine data, readjusts the career and learning plans, generating new plans as needed and sending them back to the user's device.

[0327] This series of processes allows users to obtain concrete steps to effectively advance their careers. In addition, the use of an emotion engine allows for flexible responses according to the user's psychological state.

[0328] Example 2

[0329] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0330] Conventional career and study plan proposal systems not only generate plans based on the user's skills, background, and goals, but also lack the ability to adjust the plans appropriately to take the user's emotional state into account. This makes it difficult for users to effectively advance their career or study plans while reducing the stress and burden caused by their current emotional state. Furthermore, even if they receive feedback, they lack a mechanism for appropriately readjusting the plans based on that feedback.

[0331] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0332] In this invention, the server includes means for a user to input skills, educational level, career history, and goals, means for transmitting the input information to the server, means for storing the information received by the server in a database, means for performing data analysis based on the stored information, means for generating optimal career plans and study plans based on the analysis results, means for receiving and analyzing user emotional data, means for adjusting the career plans and study plans based on the emotional data, means for transmitting the generated plans to the user's terminal, means for the user to confirm the transmitted plans, means for transmitting user feedback to the server, and means for readjusting the plans based on the feedback received by the server. This makes it possible to provide optimal career plans and study plans taking into account the user's emotional state, and to readjust the plans as necessary based on the user's feedback and emotional data.

[0333] "User" refers to an individual who uses this system to obtain a career plan and a study plan.

[0334] "Skills" refer to specific knowledge or techniques that a user possesses.

[0335] "Education level" refers to the user's educational background, such as the highest level of education and the degree obtained.

[0336] "Career" refers to the history of the jobs and tasks that a user has experienced.

[0337] "Goals" refer to the career objectives or achievements that a user wants to achieve.

[0338] "Terminal" refers to the electronic device used by a user to enter information and view plans.

[0339] "Server" refers to a central system that receives, stores, and analyzes user information, generates plans, and sends them to terminals.

[0340] "Database" refers to a data storage device for efficiently storing and managing user information and plans.

[0341] "Data analysis" refers to the process of deriving the optimal plan based on collected user information.

[0342] A "career plan" refers to the specific steps or plans a user takes to achieve their desired career goals.

[0343] A "learning plan" refers to a specific plan for a user to learn the knowledge and skills they need to acquire in order to achieve their goals.

[0344] "Emotional data" refers to information that indicates a user's emotional state, such as stress, happiness, or anxiety.

[0345] "Feedback" refers to the evaluations and comments that users make on proposed plans.

[0346] "Recalibration" refers to the process of revising and re-optimizing a plan based on user feedback and sentiment data.

[0347] "Market trends" refers to information that indicates the situation based on current economic conditions and industry trends.

[0348] "Job information" refers to information about job content and employment conditions published by companies and organizations.

[0349] "Visually easy to understand" refers to a format that is displayed graphically so that users can easily grasp the content.

[0350] This invention relates to an AI system that proposes optimal career and study plans to help users achieve their career goals. The system generates appropriate plans based on the user's skills, educational level, career history, and goals, and also has the ability to recognize the user's emotions and adjust the plans accordingly.

[0351] System configuration

[0352] 1. User Interface

[0353] Users enter information about their skills, education level, background, goals, and emotions using forms on websites and mobile applications.

[0354] 2. Data Transmission

[0355] The terminal transmits the entered information to the server using a secure protocol (e.g., HTTPS).

[0356] 3. Data Storage

[0357] The server stores the received information in a database, which allows efficient management and rapid access to large amounts of data.

[0358] 4. Data Analysis

[0359] The server runs AI algorithms based on the stored information, analyzing the user's skills, education level, background, and goals to generate optimal career and learning plans.

[0360] 5. Emotion Engine

[0361] The server uses an emotion engine to analyze emotion data from user input and dialogue history, thereby recognizing the user's emotional state and reflecting it in the career plan.

[0362] 6. Plan generation and consideration of emotional feedback

[0363] The server combines the analysis results of the AI ​​algorithm with feedback from the emotion engine to generate optimal career and study plans for the user. For example, if the user is feeling stressed, the server can include suggestions for relaxing study methods.

[0364] 7. Plan Presentation

[0365] The server encodes the generated plan in JSON format or similar and sends it to the device, which then displays the received plan in a visually easy-to-understand format.

[0366] 8. Feedback and Recalibration

[0367] The user inputs feedback on the received plan and sends it to the server, which then readjusts the career and learning plans based on this feedback and emotional data.

[0368] Specific examples

[0369] For example, consider a user who has a goal of becoming an AI engineer. The user inputs "Python" and "Basic Mathematics" as their current skills, "University Graduate" as their education level, "Data Analyst" as their career, and "Feeling Stressed" as their emotional state.

[0370] Based on this information, the server analyzes that having skills in "machine learning" and "data science" is important for becoming an AI engineer. In addition, the emotion engine recognizes that the user is feeling stressed and suggests a learning plan that includes "taking an online course" and "relaxation sessions" as a way to relax.

[0371] Prompt Sentence Examples

[0372] "Please suggest a career plan for becoming an AI engineer. Your current skills are basic Python and math, you have graduated from university, and you are working as a data analyst. Please also consider the stress you are experiencing."

[0373] By inputting these prompts into a generative AI model, a career and learning plan optimized for the user's needs and emotional state is provided. Through this process, users are provided with concrete steps to effectively advance their careers, helping them achieve their goals while reducing emotional burden.

[0374] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0375] Step 1:

[0376] Users enter information about their skills, education level, career history, goals, and emotions.

[0377] Input: User skills, education level, background, goals, emotions (e.g., "Python," "College graduate," "Data analyst," "I want to be an AI engineer," "I'm stressed").

[0378] What happens: A user fills out a form on a website or mobile application.

[0379] Output: The input information is encoded in JSON format.

[0380] Step 2:

[0381] The terminal transmits the entered information to the server using a secure protocol (e.g., HTTPS).

[0382] Input: User information encoded in JSON format.

[0383] Operation: After the send button is pressed, the device sends the data to the server using HTTPS.

[0384] Output: The encoded JSON data is sent to the server.

[0385] Step 3:

[0386] The server stores the received information in a database.

[0387] Input: User information encoded in JSON format.

[0388] How it works: The server parses the information and stores it in the appropriate tables in the database. Each item (skills, education level, career history, goals, emotional data) is associated with the user ID.

[0389] Output: The user information is saved in the database.

[0390] Step 4:

[0391] The server runs AI algorithms based on the stored information and performs data analysis.

[0392] Input: User's skills, education level, background, and goals retrieved from the database.

[0393] How it works: AI algorithms analyze this information to identify the best skill sets and learning content for your goals.

[0394] Output: Specific career and learning plans, such as "take a machine learning course" or "study data science."

[0395] Step 5:

[0396] The server receives and analyzes the user's emotion data.

[0397] Input: User emotion data retrieved from the database.

[0398] How it works: The emotion engine analyzes emotion data and identifies emotional states such as "feeling stressed."

[0399] Output: The user's emotional state (e.g., stress, happiness, anxiety).

[0400] Step 6:

[0401] The server integrates the analysis results of the AI ​​algorithm with feedback from the emotion engine to generate optimal career and learning plans.

[0402] Input: Analysis results of AI algorithm, feedback from emotion engine.

[0403] How it works: The server integrates these data and generates a plan that takes into account the user's emotional state, for example, "a study plan that includes relaxation sessions to reduce stress."

[0404] Output: Optimized career and study plans.

[0405] Step 7:

[0406] The server encodes the generated plan in JSON format and sends it to the terminal.

[0407] Input: Generated career and study plans.

[0408] How it works: The server encodes the plan into JSON format and sends it to the device.

[0409] Output: The encoded JSON data.

[0410] Step 8:

[0411] The terminal decodes the received JSON data and displays it in a visually easy-to-understand format.

[0412] Input: JSON data received from the server.

[0413] How it works: The device decodes the data and displays it in a visually understandable format such as a timeline or list. For example, "Online courses taken" or "Relaxation sessions attended."

[0414] Output: Career and study plans in a user-readable format.

[0415] Step 9:

[0416] The user inputs feedback on the plan and sends it to the server.

[0417] Input: Your rating and comments on the plan (e.g., "There's too much to learn").

[0418] How it works: The user enters their feedback and presses the submit button to send it to the server.

[0419] Output: Feedback information is sent to the server.

[0420] Step 10:

[0421] The server readjusts career and learning plans based on the feedback received.

[0422] Input: User feedback and sentiment data.

[0423] How it works: Based on feedback and sentiment data, the AI ​​algorithm is re-run to optimize the plan, for example by reducing learnings and splitting the progress schedule.

[0424] Output: A realigned career and study plan.

[0425] This series of processing flows allows users to obtain optimal career and study plans while taking into consideration their own emotional state.

[0426] (Application example 2)

[0427] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0428] Previous career and study plan generation systems did not take into account the user's emotional state or psychological burden, and were not specialized for in-store counseling support. As a result, they were unable to make optimal suggestions based on the user's emotional state, making it difficult to propose career plans that would minimize stress for users. Furthermore, because they did not support in-store counseling support, it was difficult to provide consistent service to users in-store.

[0429] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing the customer's emotions and adjusting the plan based on these emotions, means for inputting the user's skills, educational level, work history, and goals and generating optimal career and study plans based on this information, and means for transmitting the generated plans to the user's terminal and readjusting the plans based on the user's opinions. This makes it possible to propose optimal career and study plans based on the user's emotional state, and also enables counseling support in physical stores and stress reduction for users.

[0430] "User" refers to a person who uses the system.

[0431] "Skills" refers to the abilities and knowledge related to a particular task or occupation.

[0432] "Education level" refers to the level of education or academic background of the user.

[0433] "Work history" refers to the occupations and work experiences that a user has had in the past.

[0434] "Goals" refers to the career or academic goals that the user is trying to achieve in the future.

[0435] "Input means" refers to the method or device by which a user provides information about himself or herself to the system.

[0436] "Server" refers to a computer system that processes, stores, analyzes, and transmits information received from users.

[0437] "Data Storage Device" means a database or other storage device for storing user-provided information.

[0438] "Information analysis" refers to the process by which the server utilizes data received from the user to generate specific results or recommendations.

[0439] A "career plan" refers to a plan that includes procedures or steps to achieve a desired career for a user.

[0440] A "learning plan" refers to a plan for a user to acquire the knowledge and skills necessary to achieve a goal.

[0441] "Emotion analysis" refers to recognizing a user's emotions and psychological state and analyzing that information.

[0442] "Opinions" refer to feedback and requests that users provide regarding the generated plan.

[0443] "Adjustment means" refers to methods or devices that modify or improve the plan based on the user's opinions or emotional state.

[0444] "Terminal" refers to the computer or smart device that a user uses to interact with the system.

[0445] This invention relates to an AI system that proposes optimal career and study plans for users to achieve their career goals. The system generates plans based on the user's skills, educational level, work history, and goals, and also has the ability to adjust the plans by recognizing the user's emotions.

[0446] System configuration

[0447] 1. User Interface

[0448] Users input their skills, educational level, work history, and goals using devices such as smartphones or tablets. The system is intended to be used as a career counseling support tool in brick-and-mortar stores.

[0449] 2. Data Transmission

[0450] The user terminal sends the entered information to the server using a secure protocol (e.g., HTTPS), which helps protect privacy.

[0451] 3. Data Storage

[0452] The server stores the received information in a database (e.g., MySQL, PostgreSQL). Each user's information is managed efficiently and data access is rapid.

[0453] 4. Data Analysis

[0454] The server runs AI algorithms based on the stored information to generate optimal career and learning plans based on the user's skills, educational level, work history, and goals. The analysis uses AI models (e.g., machine learning libraries TensorFlow and PyTorch).

[0455] 5. Emotion analysis

[0456] The server uses an emotion engine (e.g., NLTK, TextBlob) that recognizes emotions from user input and dialogue history, thereby determining the user's psychological state and reflecting the feedback in the plan generation.

[0457] 6. Plan generation and consideration of emotional feedback

[0458] The server generates optimal career and study plans for users based on the analysis results of the AI ​​algorithm and feedback from the emotion engine. For example, if a user is feeling stressed, it will suggest relaxation methods for studying (e.g., using a meditation app or engaging in fitness activities).

[0459] 7. Presenting the plan

[0460] The server sends the generated plan to the user's terminal, where the plan is displayed in a visually easy-to-understand format.

[0461] 8. Feedback and Recalibration

[0462] The server receives feedback and emotional data provided by users and adjusts their career and learning plans accordingly, enabling the system to continuously provide optimal suggestions tailored to each individual user.

[0463] Specific examples

[0464] Specific hardware examples

[0465] Smartphones and tablets (e.g. iPhone, iPad, Samsung Galaxy)

[0466] Specific software examples

[0467] Frameworks used for REST API development (e.g., Flask, Django)

[0468] Simple sentiment analysis library (e.g. NLTK, TextBlob)

[0469] Example prompts to input to the generative AI model

[0470] What are your career goals? Tell us about your current skills, education level, and background. Also, describe your current emotional state.

[0471] This system is specialized for supporting career counseling in brick-and-mortar stores, and is able to propose optimal career plans that take into account the user's emotions. In this way, it is possible to provide users with effective career counseling with less stress.

[0472] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0473] Step 1:

[0474] The user enters information about themselves into the device, such as their skills, educational level, work history, goals, and emotional state (e.g., "I'm feeling stressed"). This information is collected through the app's user interface. The input data is structured in a standard format, such as JSON.

[0475] Step 2:

[0476] The terminal sends the entered information to the server. The data sent is encrypted using a secure protocol (e.g. HTTPS). The server stores the received data in a database. The database has a table for each user, allowing for efficient data reference.

[0477] Step 3:

[0478] The server analyzes the information stored in the data storage. Specifically, it uses AI algorithms to generate career and study plans suited to the user's skills, educational level, work history, and goals. The AI ​​algorithms used utilize machine learning frameworks (e.g., TensorFlow, PyTorch).

[0479] Step 4:

[0480] The server analyzes the user's emotions using a sentiment analysis engine. It recognizes emotions based on the input text and dialogue history. The sentiment analysis engine used uses a natural language processing library (e.g., NLTK, TextBlob).

[0481] Step 5:

[0482] The server generates optimal career and study plans based on the results of the AI ​​model analysis and feedback from emotion analysis. For example, if a user is feeling stressed, it will provide a study plan incorporating relaxation techniques. The generated plans are encoded in JSON format or similar.

[0483] Step 6:

[0484] The server sends the generated career plan and study plan to the terminal, which displays the received data in a visually easy-to-understand format (e.g., charts and lists).

[0485] Step 7:

[0486] The user checks the provided career plan and learning plan and inputs feedback. The user also inputs their evaluation of the plan and any additional requests. The feedback data is then sent back to the server.

[0487] Step 8:

[0488] The server analyzes the user's feedback and adjusts the career and learning plans as needed. This can be done using machine learning algorithms or rule-based engines. The adjusted plans are then sent back to the user's device, completing the feedback loop for the entire system.

[0489] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0490] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0491] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0492] [Second embodiment]

[0493] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0494] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0495] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0496] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0497] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0498] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0499] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0500] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0501] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0502] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0503] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0504] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0505] This invention relates to an AI system that proposes optimal career and study plans to help users achieve their career goals. This system generates and presents appropriate plans to users based on their skills, educational level, career history, and goals.

[0506] System configuration

[0507] The system configuration is as follows:

[0508] 1. User Interface

[0509] Users input their skills, education level, background, and goals, which are provided in the form of a website or mobile application.

[0510] 2. Data Transmission

[0511] The user's device sends the entered information to the server. The data is sent using a secure protocol (e.g., HTTPS).

[0512] 3. Data Storage

[0513] The server stores the received information in a database, which efficiently manages user information and allows for rapid data access.

[0514] 4. Data Analysis

[0515] The server uses the stored information to run AI algorithms that generate optimal career and study plans based on the user's skills, education level, background, and goals.

[0516] 5. Plan Generation and Presentation

[0517] The server sends the generated plan to the user's device, where the user can check the plan and learn the specific steps.

[0518] 6. Feedback and Recalibration

[0519] The server receives the feedback provided by the user and readjusts the career and study plans accordingly.

[0520] Explanation of program processing

[0521] The program processing in this system is carried out as follows.

[0522] 1. Entering and submitting information

[0523] The user inputs their skills, educational level, career history, and goals, and sends the information to the server by pressing the send button.

[0524] For example, a user enters and submits information such as "Python programming," "university graduate," "5 years of experience as a software engineer," and "I want to become an AI engineer."

[0525] 2. Receipt and storage of data

[0526] The server receives the information sent by the user and stores the information in a database.

[0527] For example, information about each user is stored in a corresponding table (eg, a skills table, an education table, a career table) in the database.

[0528] 3. Data Analysis

[0529] An AI algorithm on the server retrieves user information from the database and analyzes it.

[0530] For example, if a user's goal is to "become an AI engineer," an AI algorithm will recommend "machine learning" and "data science" as necessary skills.

[0531] 4. Plan Generation

[0532] The server generates optimal career and study plans based on the analysis results of the AI ​​algorithm.

[0533] For example, specific plans such as "take an online data science course" or "start a machine learning project in Python" are generated.

[0534] 5. Presenting the plan

[0535] The server sends the generated plan to the user's terminal, where the user can view the plan.

[0536] For example, a "data science course link" or a "list of practical project ideas" will be displayed on the user's device.

[0537] 6. Receive feedback and readjust

[0538] The user sends feedback about the plan to the server, which then readjusts the career and learning plan based on the feedback.

[0539] For example, if a user submits feedback indicating interest in a particular course, the server generates a new plan accordingly.

[0540] This process effectively enables users to take concrete steps towards their career goals.

[0541] The processing flow will be explained below.

[0542] Program processing flow

[0543] Step 1:

[0544] Users log in to the platform, either by creating an account if they are new users or by entering their login details if they are existing users.

[0545] Step 2:

[0546] Users input their skills, education level, background, and goals, clarifying their current status and future goals.

[0547] Step 3:

[0548] The device sends the entered information to the server. The data is transmitted using a secure protocol (e.g., HTTPS).

[0549] Step 4:

[0550] The server receives the information sent by the users and stores it in a database, organized by user and recorded in the appropriate tables.

[0551] Step 5:

[0552] The server retrieves the stored user information from the database and passes it to the AI ​​algorithm, which analyzes this information and generates the optimal career and study plan for the user.

[0553] Step 6:

[0554] Based on the results of the AI ​​algorithm's analysis, the server generates a specific career and learning plan, such as "take an online data science course and start a machine learning project in Python."

[0555] Step 7:

[0556] The server sends the generated plan to the user's device, where it is encoded in JSON format and received by the device.

[0557] Step 8:

[0558] The user checks the generated plan on their own device, which displays the plan in a visually easy-to-understand format.

[0559] Step 9:

[0560] The user inputs feedback about the proposed plan and sends it to the server. The feedback includes evaluation of the plan and requests for additions.

[0561] Step 10:

[0562] The server receives feedback from the user and adjusts the career and learning plans based on this feedback, generating new plans as needed and sending them back to the user's device.

[0563] This process provides users with concrete steps to effectively advance their careers.

[0564] Example 1

[0565] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0566] Conventional career and learning plan proposal systems have struggled to generate optimal plans based on a user's individual skills and goals. Furthermore, they lacked a mechanism for appropriately reflecting and adjusting user feedback on the generated plans, making it difficult to provide plans that maximize the user's benefits. Furthermore, generating plans that take into account economic trends and job information, and providing displays that are visually easy to understand, were also issues.

[0567] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0568] In this invention, the server includes: means for a user to input their abilities, educational level, work history, and goals; means for transmitting the input data to a computer; means for the computer to store the received data in a data storage device; means for processing the stored data; means for generating an optimal career plan and study plan based on the results of the information processing; means for the user to confirm the transmitted plan; means for the user to transmit the user's opinions to the computer; means for the computer to readjust the plan based on the received opinions; means for collecting economic trends and employment information and generating the user's career plan and study plan based thereon; and means for the user's information processing device to display the plan in a visually easy-to-understand format. This enables the provision of an optimal career and study plan based on the user's individual skills and goals, and also makes it easy to readjust the plan by reflecting the user's feedback. As a result, a plan that is most effective for the user can be provided.

[0569] "Ability" refers to the level of a user's technology and knowledge, including specific skills and specialized knowledge.

[0570] "Educational level" refers to the user's educational background and level of education, including classifications such as junior high school graduate, high school graduate, and university graduate.

[0571] "Work experience" refers to the occupations, industries, positions, etc. that a user has had up to now, including specific years of employment and roles.

[0572] "Goals" refer to the specific objectives and visions that a user wants to achieve in relation to their occupation or career, and include long-term goals and short-term goals.

[0573] "Computer" refers to a central control unit that processes, stores, and analyzes information sent by users, and primarily functions as a server.

[0574] "Data storage device" refers to a device for storing user information received by a computer, including a database or other storage medium.

[0575] "Information processing" refers to a series of processes that analyze and calculate stored data to derive meaningful results, and primarily involves analysis using AI algorithms.

[0576] A "career plan" refers to specific career paths and steps proposed based on the user's career goals, including methods for acquiring necessary skills and education.

[0577] A "learning plan" refers to a specific learning method or course that a user uses to acquire new skills or knowledge, including online courses and hands-on projects.

[0578] "Information processing equipment" refers to a terminal that allows a user to interact with a computer, and primarily includes devices such as smartphones and PCs.

[0579] "Opinions" means feedback or comments provided by users, including information needed to improve or adjust the Plan.

[0580] "Economic trends" refers to current market conditions and overall economic trends, including job information and industry growth forecasts.

[0581] "Employment information" refers to information related to specific job openings and job seekers in the current job market, including employment conditions and required skills.

[0582] "Visually easy to understand" refers to a display format that allows users to intuitively understand the proposed plan, including graphical interfaces and infographics.

[0583] MODE FOR CARRYING OUT THE INVENTION

[0584] This invention relates to a system that proposes optimal career and study plans based on the abilities, educational level, work history, and goals input by a user. This system is realized mainly using a user terminal, a server, a data storage device, and various software components.

[0585] User terminal

[0586] A user terminal is a device that a user uses to access a system and input the necessary information. This mainly includes PCs, smartphones, and tablets. Users input information into a form displayed on the terminal screen.

[0587] For example, enter the following information:

[0588] Skills: Python programming

[0589] Education level: University graduate

[0590] Work Experience: 5 years of experience as a software engineer

[0591] Goal: I want to become an AI engineer

[0592] server

[0593] The server receives the information sent by the user and stores it in a data storage device. The data from the user is transmitted via a secure protocol (e.g., HTTPS). The received data is stored in a database.

[0594] Data Storage Device

[0595] Data storage is a system that organizes user information appropriately and makes it quickly accessible, using a relational database management system (RDBMS) or a NoSQL database.

[0596] Information Processing

[0597] The server retrieves the information stored in the data storage device and analyzes it using AI algorithms. These algorithms utilize generative AI models to recommend skills and learning resources needed to achieve the user's goals. Data analysis software such as Python and R is used on the server.

[0598] for example,

[0599] If a user's goal is to "become an AI engineer," the AI ​​algorithm will determine that skills like "machine learning" and "data science" are required, and will then recommend appropriate online courses and projects.

[0600] Plan Generation

[0601] Based on the analysis results of the AI ​​algorithm, the server generates a career plan and study plan tailored to each user. The plan includes specific steps and is presented in a form that the user can follow.

[0602] For example, specific plans such as "take an online data science course" or "start a machine learning project in Python" are generated.

[0603] Presenting the plan

[0604] The server sends the generated plan to the user's device, where the user can view the plan on their own device. Specifically, the plan displays "Data Science Course Links" and "Practical Project Idea List," allowing the user to access these resources.

[0605] Receive feedback and readjust

[0606] The user provides feedback on the proposed plan, for example, by inputting specific opinions such as "I'm interested in this course" or "This step is too difficult." The server receives this feedback and readjusts the plan using an AI algorithm. The adjusted plan is then sent back to the user's device, where the user can review the new proposal.

[0607] Example prompt

[0608] As a concrete example, the following prompts can be provided to a generative AI model:

[0609] "If a user sets a goal of 'I want to become an AI engineer,' please provide them with the necessary skills and a recommended learning plan."

[0610] "How do we generate the optimal learning plan for a user with Python programming skills, a college degree, and five years of software engineering experience?"

[0611] By implementing this invention, users are empowered to take concrete and effective steps towards their career goals.

[0612] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0613] Step 1:

[0614] User enters information and submits

[0615] The user enters the following information into a form on their device: ability (e.g., Python programming), level of education (e.g., university graduate), work experience (e.g., 5 years of experience as a software engineer), and goal (e.g., want to become an AI engineer). After entering the information, they press the "Submit" button, and this information is sent to the server using HTTPS.

[0616] Input: User skills, education level, work history, goals

[0617] Output: User information sent to the server

[0618] Step 2:

[0619] The server receives and stores the data

[0620] The server receives the data sent by the user and stores it in a data storage device. In the database, skill information is stored in a skill table, education level in an education table, and work history in a work history table.

[0621] Input: User information sent to the server

[0622] Output: User information stored in the database

[0623] Step 3:

[0624] The server analyzes the data

[0625] The server retrieves user information stored in the database and analyzes it using an AI algorithm. The AI ​​algorithm then uses a generative AI model to recommend skills and learning resources necessary to achieve the user's goals. For example, if the goal is to "become an AI engineer," the analysis results would include "machine learning" and "data science."

[0626] Input: User information stored in the database

[0627] Output: Recommendations for optimal skills and learning resources

[0628] Step 4:

[0629] The server generates a plan

[0630] Based on the results of the AI ​​algorithm's analysis, the server generates a personalized career and learning plan for each user, with specific steps such as "take an online data science course" or "start a machine learning project in Python."

[0631] Input: Recommendations for optimal skills and learning resources

[0632] Output: Generated career and study plans

[0633] Step 5:

[0634] The server presents the plan to the user

[0635] The server sends the generated plan to the user's device, where the user can view it and see specific links and steps in a visually understandable format. For example, "Data Science Course Links" and "Practical Project Idea List" are displayed.

[0636] Input: Generated career and study plans

[0637] Output: The plan displayed on the user's device

[0638] Step 6:

[0639] Users provide feedback and readjust

[0640] The user provides feedback on the presented plan, such as "I'm interested in this course" or "This step is too difficult." The server receives this feedback and readjusts the plan using an AI algorithm. The adjusted plan is then sent back to the user's device.

[0641] Input: User feedback

[0642] Output: Realigned career and study plans

[0643] (Application example 1)

[0644] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0645] Currently, there are systems that suggest career and learning plans, but there is a lack of systems that support payment management and fund tracking for related learning courses and services. Furthermore, the ability to adjust plans based on user feedback is insufficient, making it difficult to flexibly respond to user needs.

[0646] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0647] In this invention, the server includes: a means for a user to input skills, educational level, career history, and goals; a means for transmitting the input information to the server; a means for performing data analysis based on the stored information; a means for generating an optimal career plan and learning plan based on the analysis results; a means for managing payments for learning courses and services based on the proposed plan; and a means for providing and tracking the use of funds for achieving the career plan. This allows users to centrally manage payments for learning courses and services to implement their optimal career plan and track the use of funds. Furthermore, by readjusting the plan based on user feedback, the plan can be flexibly changed to meet needs.

[0648] "User" refers to any individual or legal entity that uses the System.

[0649] "Skills" refer to the abilities and knowledge required to perform a particular task or activity.

[0650] "Education level" refers to the educational background and learning progress of the user at an educational institution.

[0651] A "career history" is a record of a user's work history and professional experience.

[0652] "Goals" refer to the specific career or learning goals that a user is trying to achieve.

[0653] "Server" refers to an information processing device that receives and stores data from users and processes that data.

[0654] "Database" means the data structures and software systems used to manage and store User information.

[0655] "Data analysis" refers to the analytical process that the system uses to generate optimal career and study plans based on the input user information.

[0656] "Career plan" refers to the plan and specific steps a user takes to reach the career or job they are aiming for.

[0657] "Study Plan" means the learning plan and specific courses that a User takes to acquire the necessary skills toward their career goals.

[0658] "Payment" refers to the act of a user paying for a learning course or service provided.

[0659] "Funding Tracking" refers to the management and recording of funds a user has invested to achieve their career goals.

[0660] "Feedback" refers to the opinions and evaluations provided by users regarding proposed plans.

[0661] "Readjustment" refers to modifying or changing existing career or study plans based on feedback received from users.

[0662] Overall system configuration

[0663] This invention is an AI system for supporting users in achieving their career goals, and in particular has a payment management function related to career and learning plan proposals. The system includes the following main components:

[0664] User Interface

[0665] Data transmission

[0666] Data Storage

[0667] Data analysis

[0668] Plan generation and presentation

[0669] Feedback and Recalibration

[0670] Payment Management

[0671] Funds Tracking

[0672] User Interface

[0673] Users are provided with an interface to input their skills, education level, background, and goals, which can be entered through a website or mobile application.

[0674] Data Transmission and Storage

[0675] The information entered by the user is sent to the server using a secure protocol (e.g. HTTPS), and the server stores the received information in a database for efficient management.

[0676] Data analysis and plan generation

[0677] The server runs AI algorithms based on the stored information to generate optimal career and learning plans based on the user's skills, education level, background, and goals. The AI ​​models used include the Logistic Regression model.

[0678] Plan presentation and feedback

[0679] The generated plan is sent to the user's device for review, and the user can provide feedback on the plan, which the server then uses to adjust the plan.

[0680] Payment Management

[0681] Payment for the proposed course or service is managed within the system, and payment is completed by entering payment information.

[0682] Funds Tracking

[0683] It also provides a tracking function for the use of funds invested in achieving career plans, allowing users to manage their funds efficiently.

[0684] Adding specific examples to the description

[0685] For example, a user enters the information "Python programming", "college graduate", "5 years of experience as a software engineer", and "I want to become an AI engineer", and sends the following prompt to the server:

[0686] Skills: Python programming

[0687] Education level: University graduate

[0688] Experience: 5 years of experience as a software engineer

[0689] Goal: I want to become an AI engineer

[0690] This information is stored in a database, and the AI ​​model performs the necessary analysis to generate a specific career plan, such as "take an online data science course" or "start a machine learning project in Python." This plan is then presented to the user, who can then make course payments and manage their finances centrally based on the proposal.

[0691] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0692] Step 1:

[0693] Users enter their skills, education level, background, and goals.

[0694] The input information could be, for example, "Python programming," "university graduate," "5 years of experience as a software engineer," or "I want to become an AI engineer." This information is provided through a user interface (website or mobile application).

[0695] Step 2:

[0696] The user's terminal transmits the input information to the server.

[0697] This uses a secure protocol such as HTTPS.

[0698] Input data is sent and the server receives the data.

[0699] Step 3:

[0700] The server stores the received information in a database.

[0701] The data stored includes skill information, education level, career history, and goals, making it easier to manage user information on the database.

[0702] Step 4:

[0703] An AI algorithm on the server retrieves user information from the database and performs data analysis.

[0704] Specifically, it uses AI models (e.g., logistic regression) to analyze the user's skills and goals, which then triggers the creation of a career and learning plan tailored to the user.

[0705] Step 5:

[0706] The server generates a career plan and a study plan based on the analysis results.

[0707] For example, the generated plan might include "Take an online data science course" or "Start a machine learning project in Python," giving users a clear understanding of the steps involved.

[0708] Step 6:

[0709] The generated plan is sent to the user's terminal.

[0710] The user's device displays this received information in a visually easy-to-understand format, such as course links or a list of project ideas on the user interface.

[0711] Step 7:

[0712] The user reviews the generated plan and provides feedback.

[0713] The feedback includes evaluation of the plan and suggestions for improvement, etc. The feedback is sent back to the server.

[0714] Step 8:

[0715] The server readjusts the plan based on the feedback it receives.

[0716] A new, optimized plan is generated based on the user's opinions, allowing for flexible changes to the plan according to the user's needs.

[0717] Step 9:

[0718] The server manages payments for learning courses and services based on the proposed plan.

[0719] Once the user enters their payment information, the payment is completed and stored in a database, facilitating access to related courses and services.

[0720] Step 10:

[0721] The server provides usage and tracking of funds invested in achieving career plans.

[0722] Users can view the progress and usage history of their funds, which allows them to manage their funds according to plan.

[0723] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0724] This invention relates to an AI system that proposes optimal career and study plans to help users achieve their career goals. The system generates appropriate plans based on the user's skills, educational level, career history, and goals, and also has the ability to recognize the user's emotions and adjust the plans accordingly.

[0725] System configuration

[0726] The system configuration is as follows:

[0727] 1. User Interface

[0728] Users input their skills, education level, background, and goals, which are provided in the form of a website or mobile application.

[0729] 2. Data Transmission

[0730] The user's device sends the entered information to the server. The data is transmitted using a secure protocol (e.g., HTTPS).

[0731] 3. Data Storage

[0732] The server stores the received information in a database, which efficiently manages user information and allows for rapid data access.

[0733] 4. Data Analysis

[0734] The server uses the stored information to run AI algorithms that generate optimal career and study plans based on the user's skills, education level, background, and goals.

[0735] 5. Emotion Engine

[0736] It is equipped with an emotion engine that recognizes the user's emotions. The emotion engine analyzes emotions from the user's input and dialogue history.

[0737] 6. Plan generation and consideration of emotional feedback

[0738] The server takes into account the analysis results of the AI ​​algorithm and feedback from the emotion engine to generate the optimal career and study plans for the user.

[0739] For example, if a user is feeling stressed, suggestions for relaxing study methods can be included.

[0740] 7. Plan Presentation

[0741] The server sends the generated plan to the user's device, where the user can view the plan and learn the specific steps.

[0742] 8. Feedback and Recalibration

[0743] The server receives the feedback and emotional data provided by the user and readjusts the career and learning plans accordingly.

[0744] Explanation of program processing

[0745] The program processing in this system is carried out as follows.

[0746] 1. Entering and submitting information

[0747] Users input their skills, education level, background, goals, as well as emotional input (e.g., "I'm feeling stressed").

[0748] This information is sent to the server by pressing the send button.

[0749] 2. Receipt and storage of data

[0750] The server receives the information sent by the user and stores it in a database.

[0751] The information is organized for each user and recorded in the appropriate tables.

[0752] 3. Data Analysis

[0753] An AI algorithm on the server retrieves user information from the database and analyzes it.

[0754] For example, if a user's goal is to "become an AI engineer," the system will recommend "machine learning" and "data science" as necessary skills.

[0755] 4. Emotion Data Analysis

[0756] The server's emotion engine analyzes the user's emotion data and determines the user's current emotional state.

[0757] 5. Plan Generation

[0758] The server generates optimal career and study plans based on the analysis results of the AI ​​algorithm and feedback from the emotion engine.

[0759] For example, specific plans such as "take an online data science course" or "start a machine learning project in Python" are generated.

[0760] 6. Presenting the plan

[0761] The server sends the generated plan to the user's device, where it is encoded in JSON format and received by the device.

[0762] 7. User Confirms Plan

[0763] The user checks the generated plan on their own device, which displays the plan in a visually easy-to-understand format.

[0764] 8. Receive feedback and readjust

[0765] The user inputs feedback about the plan and sends it to the server. The feedback includes evaluation of the plan and requests for additions.

[0766] The server receives feedback and emotional data from users and readjusts their career and learning plans based on this.

[0767] This series of processes allows users to obtain concrete steps to effectively advance their careers. In addition, the emotion engine reduces the user's psychological burden and provides more appropriate suggestions.

[0768] The processing flow will be explained below.

[0769] Program processing flow

[0770] Step 1:

[0771] Users log in to the platform, either by creating an account if they are new users or by entering their login details if they are existing users.

[0772] Step 2:

[0773] Users input their skills, education level, career history, goals, and current emotional state. For example, they input "Python programming" as a skill, "university graduate" as an education level, "5 years of experience as a software engineer" as a career history, "I want to become an AI engineer" as a goal, and "I feel stressed" as an emotional state.

[0774] Step 3:

[0775] The device sends the entered information to the server. The data is transmitted using a secure protocol (e.g., HTTPS).

[0776] Step 4:

[0777] The server receives the information sent by the users and stores it in a database, organized by user and recorded in the appropriate tables.

[0778] Step 5:

[0779] The server retrieves the stored user information from the database and passes it to the AI ​​algorithm, which analyzes this information and generates the optimal career and study plan for the user.

[0780] Step 6:

[0781] The server's emotion engine analyzes the user's emotion data. For example, if the user is "feeling stressed," the emotion engine analyzes the data and understands the user's psychological state.

[0782] Step 7:

[0783] Based on the analysis results of the AI ​​algorithm and feedback from the emotion engine, the server generates specific career and learning plans, such as "take an online data science course and start a machine learning project in Python," as well as "suggestions for relaxing study methods."

[0784] Step 8:

[0785] The server sends the generated plan to the user's device, where it is encoded in JSON format and received by the device.

[0786] Step 9:

[0787] The user can then view the generated plan on their device. The device displays the plan in a visually easy-to-understand format. For example, the user's device displays a "Data Science course link" and a "List of ideas for practical projects."

[0788] Step 10:

[0789] The user inputs feedback about the presented plan and sends it to the server. The feedback includes an evaluation of the plan and requests for additions. For example, the user can send feedback such as "The course is too difficult."

[0790] Step 11:

[0791] The server receives feedback from the user and, together with the emotion engine data, readjusts the career and learning plans, generating new plans as needed and sending them back to the user's device.

[0792] This series of processes allows users to obtain concrete steps to effectively advance their careers. In addition, the use of an emotion engine allows for flexible responses according to the user's psychological state.

[0793] Example 2

[0794] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0795] Conventional career and study plan proposal systems not only generate plans based on the user's skills, background, and goals, but also lack the ability to adjust the plans appropriately to take the user's emotional state into account. This makes it difficult for users to effectively advance their career or study plans while reducing the stress and burden caused by their current emotional state. Furthermore, even if they receive feedback, they lack a mechanism for appropriately readjusting the plans based on that feedback.

[0796] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0797] In this invention, the server includes means for a user to input skills, educational level, career history, and goals, means for transmitting the input information to the server, means for storing the information received by the server in a database, means for performing data analysis based on the stored information, means for generating optimal career plans and study plans based on the analysis results, means for receiving and analyzing user emotional data, means for adjusting the career plans and study plans based on the emotional data, means for transmitting the generated plans to the user's terminal, means for the user to confirm the transmitted plans, means for transmitting user feedback to the server, and means for readjusting the plans based on the feedback received by the server. This makes it possible to provide optimal career plans and study plans taking into account the user's emotional state, and to readjust the plans as necessary based on the user's feedback and emotional data.

[0798] "User" refers to an individual who uses this system to obtain a career plan and a study plan.

[0799] "Skills" refer to specific knowledge or techniques that a user possesses.

[0800] "Education level" refers to the user's educational background, such as the highest level of education and the degree obtained.

[0801] "Career" refers to the history of the jobs and tasks that a user has experienced.

[0802] "Goals" refer to the career objectives or achievements that a user wants to achieve.

[0803] "Terminal" refers to the electronic device used by a user to enter information and view plans.

[0804] "Server" refers to a central system that receives, stores, and analyzes user information, generates plans, and sends them to terminals.

[0805] "Database" refers to a data storage device for efficiently storing and managing user information and plans.

[0806] "Data analysis" refers to the process of deriving the optimal plan based on collected user information.

[0807] A "career plan" refers to the specific steps or plans a user takes to achieve their desired career goals.

[0808] A "learning plan" refers to a specific plan for a user to learn the knowledge and skills they need to acquire in order to achieve their goals.

[0809] "Emotional data" refers to information that indicates a user's emotional state, such as stress, happiness, or anxiety.

[0810] "Feedback" refers to the evaluations and comments that users make on proposed plans.

[0811] "Recalibration" refers to the process of revising and re-optimizing a plan based on user feedback and sentiment data.

[0812] "Market trends" refers to information that indicates the situation based on current economic conditions and industry trends.

[0813] "Job information" refers to information about job content and employment conditions published by companies and organizations.

[0814] "Visually easy to understand" refers to a format that is displayed graphically so that users can easily grasp the content.

[0815] This invention relates to an AI system that proposes optimal career and study plans to help users achieve their career goals. The system generates appropriate plans based on the user's skills, educational level, career history, and goals, and also has the ability to recognize the user's emotions and adjust the plans accordingly.

[0816] System configuration

[0817] 1. User Interface

[0818] Users enter information about their skills, education level, background, goals, and emotions using forms on websites and mobile applications.

[0819] 2. Data Transmission

[0820] The terminal transmits the entered information to the server using a secure protocol (e.g., HTTPS).

[0821] 3. Data Storage

[0822] The server stores the received information in a database, which allows efficient management and rapid access to large amounts of data.

[0823] 4. Data Analysis

[0824] The server runs AI algorithms based on the stored information, analyzing the user's skills, education level, background, and goals to generate optimal career and learning plans.

[0825] 5. Emotion Engine

[0826] The server uses an emotion engine to analyze emotion data from user input and dialogue history, thereby recognizing the user's emotional state and reflecting it in the career plan.

[0827] 6. Plan generation and consideration of emotional feedback

[0828] The server combines the analysis results of the AI ​​algorithm with feedback from the emotion engine to generate optimal career and study plans for the user. For example, if the user is feeling stressed, the server can include suggestions for relaxing study methods.

[0829] 7. Plan Presentation

[0830] The server encodes the generated plan in JSON format or similar and sends it to the device, which then displays the received plan in a visually easy-to-understand format.

[0831] 8. Feedback and Recalibration

[0832] The user inputs feedback on the received plan and sends it to the server, which then readjusts the career and learning plans based on this feedback and emotional data.

[0833] Specific examples

[0834] For example, consider a user who has a goal of becoming an AI engineer. The user inputs "Python" and "Basic Mathematics" as their current skills, "University Graduate" as their education level, "Data Analyst" as their career, and "Feeling Stressed" as their emotional state.

[0835] Based on this information, the server analyzes that having skills in "machine learning" and "data science" is important for becoming an AI engineer. In addition, the emotion engine recognizes that the user is feeling stressed and suggests a learning plan that includes "taking an online course" and "relaxation sessions" as a way to relax.

[0836] Prompt Sentence Examples

[0837] "Please suggest a career plan for becoming an AI engineer. Your current skills are basic Python and math, you have graduated from university, and you are working as a data analyst. Please also consider the stress you are experiencing."

[0838] By inputting these prompts into a generative AI model, a career and learning plan optimized for the user's needs and emotional state is provided. Through this process, users are provided with concrete steps to effectively advance their careers, helping them achieve their goals while reducing emotional burden.

[0839] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0840] Step 1:

[0841] Users enter information about their skills, education level, career history, goals, and emotions.

[0842] Input: User skills, education level, background, goals, emotions (e.g., "Python," "College graduate," "Data analyst," "I want to be an AI engineer," "I'm stressed").

[0843] What happens: A user fills out a form on a website or mobile application.

[0844] Output: The input information is encoded in JSON format.

[0845] Step 2:

[0846] The terminal transmits the entered information to the server using a secure protocol (e.g., HTTPS).

[0847] Input: User information encoded in JSON format.

[0848] Operation: After the send button is pressed, the device sends the data to the server using HTTPS.

[0849] Output: The encoded JSON data is sent to the server.

[0850] Step 3:

[0851] The server stores the received information in a database.

[0852] Input: User information encoded in JSON format.

[0853] How it works: The server parses the information and stores it in the appropriate tables in the database. Each item (skills, education level, career history, goals, emotional data) is associated with the user ID.

[0854] Output: The user information is saved in the database.

[0855] Step 4:

[0856] The server runs AI algorithms based on the stored information and performs data analysis.

[0857] Input: User's skills, education level, background, and goals retrieved from the database.

[0858] How it works: AI algorithms analyze this information to identify the best skill sets and learning content for your goals.

[0859] Output: Specific career and learning plans, such as "take a machine learning course" or "study data science."

[0860] Step 5:

[0861] The server receives and analyzes the user's emotion data.

[0862] Input: User emotion data retrieved from the database.

[0863] How it works: The emotion engine analyzes emotion data and identifies emotional states such as "feeling stressed."

[0864] Output: The user's emotional state (e.g., stress, happiness, anxiety).

[0865] Step 6:

[0866] The server integrates the analysis results of the AI ​​algorithm with feedback from the emotion engine to generate optimal career and learning plans.

[0867] Input: Analysis results of AI algorithm, feedback from emotion engine.

[0868] How it works: The server integrates these data and generates a plan that takes into account the user's emotional state, for example, "a study plan that includes relaxation sessions to reduce stress."

[0869] Output: Optimized career and study plans.

[0870] Step 7:

[0871] The server encodes the generated plan in JSON format and sends it to the terminal.

[0872] Input: Generated career and study plans.

[0873] How it works: The server encodes the plan into JSON format and sends it to the device.

[0874] Output: The encoded JSON data.

[0875] Step 8:

[0876] The terminal decodes the received JSON data and displays it in a visually easy-to-understand format.

[0877] Input: JSON data received from the server.

[0878] How it works: The device decodes the data and displays it in a visually understandable format such as a timeline or list. For example, "Online courses taken" or "Relaxation sessions attended."

[0879] Output: Career and study plans in a user-readable format.

[0880] Step 9:

[0881] The user inputs feedback on the plan and sends it to the server.

[0882] Input: Your rating and comments on the plan (e.g., "There's too much to learn").

[0883] How it works: The user enters their feedback and presses the submit button to send it to the server.

[0884] Output: Feedback information is sent to the server.

[0885] Step 10:

[0886] The server readjusts career and learning plans based on the feedback received.

[0887] Input: User feedback and sentiment data.

[0888] How it works: Based on feedback and sentiment data, the AI ​​algorithm is re-run to optimize the plan, for example by reducing learnings and splitting the progress schedule.

[0889] Output: A realigned career and study plan.

[0890] This series of processing flows allows users to obtain optimal career and study plans while taking into consideration their own emotional state.

[0891] (Application example 2)

[0892] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0893] Previous career and study plan generation systems did not take into account the user's emotional state or psychological burden, and were not specialized for in-store counseling support. As a result, they were unable to make optimal suggestions based on the user's emotional state, making it difficult to propose career plans that would minimize stress for users. Furthermore, because they did not support in-store counseling support, it was difficult to provide consistent service to users in-store.

[0894] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing the customer's emotions and adjusting the plan based on these emotions, means for inputting the user's skills, educational level, work history, and goals and generating optimal career and study plans based on this information, and means for transmitting the generated plans to the user's terminal and readjusting the plans based on the user's opinions. This makes it possible to propose optimal career and study plans based on the user's emotional state, and also enables counseling support in physical stores and stress reduction for users.

[0895] "User" refers to a person who uses the system.

[0896] "Skills" refers to the abilities and knowledge related to a particular task or occupation.

[0897] "Education level" refers to the level of education or academic background of the user.

[0898] "Work history" refers to the occupations and work experiences that a user has had in the past.

[0899] "Goals" refers to the career or academic goals that the user is trying to achieve in the future.

[0900] "Input means" refers to the method or device by which a user provides information about himself or herself to the system.

[0901] "Server" refers to a computer system that processes, stores, analyzes, and transmits information received from users.

[0902] "Data Storage Device" means a database or other storage device for storing user-provided information.

[0903] "Information analysis" refers to the process by which the server utilizes data received from the user to generate specific results or recommendations.

[0904] A "career plan" refers to a plan that includes procedures or steps to achieve a desired career for a user.

[0905] A "learning plan" refers to a plan for a user to acquire the knowledge and skills necessary to achieve a goal.

[0906] "Emotion analysis" refers to recognizing a user's emotions and psychological state and analyzing that information.

[0907] "Opinions" refer to feedback and requests that users provide regarding the generated plan.

[0908] "Adjustment means" refers to methods or devices that modify or improve the plan based on the user's opinions or emotional state.

[0909] "Terminal" refers to the computer or smart device that a user uses to interact with the system.

[0910] This invention relates to an AI system that proposes optimal career and study plans for users to achieve their career goals. The system generates plans based on the user's skills, educational level, work history, and goals, and also has the ability to adjust the plans by recognizing the user's emotions.

[0911] System configuration

[0912] 1. User Interface

[0913] Users input their skills, educational level, work history, and goals using devices such as smartphones or tablets. The system is intended to be used as a career counseling support tool in brick-and-mortar stores.

[0914] 2. Data Transmission

[0915] The user terminal sends the entered information to the server using a secure protocol (e.g., HTTPS), which helps protect privacy.

[0916] 3. Data Storage

[0917] The server stores the received information in a database (e.g., MySQL, PostgreSQL). Each user's information is managed efficiently and data access is rapid.

[0918] 4. Data Analysis

[0919] The server runs AI algorithms based on the stored information to generate optimal career and learning plans based on the user's skills, educational level, work history, and goals. The analysis uses AI models (e.g., machine learning libraries TensorFlow and PyTorch).

[0920] 5. Emotion analysis

[0921] The server uses an emotion engine (e.g., NLTK, TextBlob) that recognizes emotions from user input and dialogue history, thereby determining the user's psychological state and reflecting the feedback in the plan generation.

[0922] 6. Plan generation and consideration of emotional feedback

[0923] The server generates optimal career and study plans for users based on the analysis results of the AI ​​algorithm and feedback from the emotion engine. For example, if a user is feeling stressed, it will suggest relaxation methods for studying (e.g., using a meditation app or engaging in fitness activities).

[0924] 7. Presenting the plan

[0925] The server sends the generated plan to the user's terminal, where the plan is displayed in a visually easy-to-understand format.

[0926] 8. Feedback and Recalibration

[0927] The server receives feedback and emotional data provided by users and adjusts their career and learning plans accordingly, enabling the system to continuously provide optimal suggestions tailored to each individual user.

[0928] Specific examples

[0929] Specific hardware examples

[0930] Smartphones and tablets (e.g. iPhone, iPad, Samsung Galaxy)

[0931] Specific software examples

[0932] Frameworks used for REST API development (e.g., Flask, Django)

[0933] Simple sentiment analysis library (e.g. NLTK, TextBlob)

[0934] Example prompts to input to the generative AI model

[0935] What are your career goals? Tell us about your current skills, education level, and background. Also, describe your current emotional state.

[0936] This system is specialized for supporting career counseling in brick-and-mortar stores, and is able to propose optimal career plans that take into account the user's emotions. In this way, it is possible to provide users with effective career counseling with less stress.

[0937] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0938] Step 1:

[0939] The user enters information about themselves into the device, such as their skills, educational level, work history, goals, and emotional state (e.g., "I'm feeling stressed"). This information is collected through the app's user interface. The input data is structured in a standard format, such as JSON.

[0940] Step 2:

[0941] The terminal sends the entered information to the server. The data sent is encrypted using a secure protocol (e.g. HTTPS). The server stores the received data in a database. The database has a table for each user, allowing for efficient data reference.

[0942] Step 3:

[0943] The server analyzes the information stored in the data storage. Specifically, it uses AI algorithms to generate career and study plans suited to the user's skills, educational level, work history, and goals. The AI ​​algorithms used utilize machine learning frameworks (e.g., TensorFlow, PyTorch).

[0944] Step 4:

[0945] The server analyzes the user's emotions using a sentiment analysis engine. It recognizes emotions based on the input text and dialogue history. The sentiment analysis engine used uses a natural language processing library (e.g., NLTK, TextBlob).

[0946] Step 5:

[0947] The server generates optimal career and study plans based on the results of the AI ​​model analysis and feedback from emotion analysis. For example, if a user is feeling stressed, it will provide a study plan incorporating relaxation techniques. The generated plans are encoded in JSON format or similar.

[0948] Step 6:

[0949] The server sends the generated career plan and study plan to the terminal, which displays the received data in a visually easy-to-understand format (e.g., charts and lists).

[0950] Step 7:

[0951] The user checks the provided career plan and learning plan and inputs feedback. The user also inputs their evaluation of the plan and any additional requests. The feedback data is then sent back to the server.

[0952] Step 8:

[0953] The server analyzes the user's feedback and adjusts the career and learning plans as needed. This can be done using machine learning algorithms or rule-based engines. The adjusted plans are then sent back to the user's device, completing the feedback loop for the entire system.

[0954] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0955] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0956] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0957] [Third embodiment]

[0958] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0959] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0960] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0961] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0962] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0963] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0964] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0965] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0966] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0967] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0968] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0969] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0970] This invention relates to an AI system that proposes optimal career and study plans to help users achieve their career goals. This system generates and presents appropriate plans to users based on their skills, educational level, career history, and goals.

[0971] System configuration

[0972] The system configuration is as follows:

[0973] 1. User Interface

[0974] Users input their skills, education level, background, and goals, which are provided in the form of a website or mobile application.

[0975] 2. Data Transmission

[0976] The user's device sends the entered information to the server. The data is sent using a secure protocol (e.g., HTTPS).

[0977] 3. Data Storage

[0978] The server stores the received information in a database, which efficiently manages user information and allows for rapid data access.

[0979] 4. Data Analysis

[0980] The server uses the stored information to run AI algorithms that generate optimal career and study plans based on the user's skills, education level, background, and goals.

[0981] 5. Plan Generation and Presentation

[0982] The server sends the generated plan to the user's device, where the user can check the plan and learn the specific steps.

[0983] 6. Feedback and Recalibration

[0984] The server receives the feedback provided by the user and readjusts the career and study plans accordingly.

[0985] Explanation of program processing

[0986] The program processing in this system is carried out as follows.

[0987] 1. Entering and submitting information

[0988] The user inputs their skills, educational level, career history, and goals, and sends the information to the server by pressing the send button.

[0989] For example, a user enters and submits information such as "Python programming," "university graduate," "5 years of experience as a software engineer," and "I want to become an AI engineer."

[0990] 2. Receipt and storage of data

[0991] The server receives the information sent by the user and stores the information in a database.

[0992] For example, information about each user is stored in a corresponding table (eg, a skills table, an education table, a career table) in the database.

[0993] 3. Data Analysis

[0994] An AI algorithm on the server retrieves user information from the database and analyzes it.

[0995] For example, if a user's goal is to "become an AI engineer," an AI algorithm will recommend "machine learning" and "data science" as necessary skills.

[0996] 4. Plan Generation

[0997] The server generates optimal career and study plans based on the analysis results of the AI ​​algorithm.

[0998] For example, specific plans such as "take an online data science course" or "start a machine learning project in Python" are generated.

[0999] 5. Presenting the plan

[1000] The server sends the generated plan to the user's terminal, where the user can view the plan.

[1001] For example, a "data science course link" or a "list of practical project ideas" will be displayed on the user's device.

[1002] 6. Receive feedback and readjust

[1003] The user sends feedback about the plan to the server, which then readjusts the career and learning plan based on the feedback.

[1004] For example, if a user submits feedback indicating interest in a particular course, the server generates a new plan accordingly.

[1005] This process effectively enables users to take concrete steps towards their career goals.

[1006] The processing flow will be explained below.

[1007] Program processing flow

[1008] Step 1:

[1009] Users log in to the platform, either by creating an account if they are new users or by entering their login details if they are existing users.

[1010] Step 2:

[1011] Users input their skills, education level, background, and goals, clarifying their current status and future goals.

[1012] Step 3:

[1013] The device sends the entered information to the server. The data is transmitted using a secure protocol (e.g., HTTPS).

[1014] Step 4:

[1015] The server receives the information sent by the users and stores it in a database, organized by user and recorded in the appropriate tables.

[1016] Step 5:

[1017] The server retrieves the stored user information from the database and passes it to the AI ​​algorithm, which analyzes this information and generates the optimal career and study plan for the user.

[1018] Step 6:

[1019] Based on the results of the AI ​​algorithm's analysis, the server generates a specific career and learning plan, such as "take an online data science course and start a machine learning project in Python."

[1020] Step 7:

[1021] The server sends the generated plan to the user's device, where it is encoded in JSON format and received by the device.

[1022] Step 8:

[1023] The user checks the generated plan on their own device, which displays the plan in a visually easy-to-understand format.

[1024] Step 9:

[1025] The user inputs feedback about the proposed plan and sends it to the server. The feedback includes evaluation of the plan and requests for additions.

[1026] Step 10:

[1027] The server receives feedback from the user and adjusts the career and learning plans based on this feedback, generating new plans as needed and sending them back to the user's device.

[1028] This process provides users with concrete steps to effectively advance their careers.

[1029] Example 1

[1030] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1031] Conventional career and learning plan proposal systems have struggled to generate optimal plans based on a user's individual skills and goals. Furthermore, they lacked a mechanism for appropriately reflecting and adjusting user feedback on the generated plans, making it difficult to provide plans that maximize the user's benefits. Furthermore, generating plans that take into account economic trends and job information, and providing displays that are visually easy to understand, were also issues.

[1032] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1033] In this invention, the server includes: means for a user to input their abilities, educational level, work history, and goals; means for transmitting the input data to a computer; means for the computer to store the received data in a data storage device; means for processing the stored data; means for generating an optimal career plan and study plan based on the results of the information processing; means for the user to confirm the transmitted plan; means for the user to transmit the user's opinions to the computer; means for the computer to readjust the plan based on the received opinions; means for collecting economic trends and employment information and generating the user's career plan and study plan based thereon; and means for the user's information processing device to display the plan in a visually easy-to-understand format. This enables the provision of an optimal career and study plan based on the user's individual skills and goals, and also makes it easy to readjust the plan by reflecting the user's feedback. As a result, a plan that is most effective for the user can be provided.

[1034] "Ability" refers to the level of a user's technology and knowledge, including specific skills and specialized knowledge.

[1035] "Educational level" refers to the user's educational background and level of education, including classifications such as junior high school graduate, high school graduate, and university graduate.

[1036] "Work experience" refers to the occupations, industries, positions, etc. that a user has had up to now, including specific years of employment and roles.

[1037] "Goals" refer to the specific objectives and visions that a user wants to achieve in relation to their occupation or career, and include long-term goals and short-term goals.

[1038] "Computer" refers to a central control unit that processes, stores, and analyzes information sent by users, and primarily functions as a server.

[1039] "Data storage device" refers to a device for storing user information received by a computer, including a database or other storage medium.

[1040] "Information processing" refers to a series of processes that analyze and calculate stored data to derive meaningful results, and primarily involves analysis using AI algorithms.

[1041] A "career plan" refers to specific career paths and steps proposed based on the user's career goals, including methods for acquiring necessary skills and education.

[1042] A "learning plan" refers to a specific learning method or course that a user uses to acquire new skills or knowledge, including online courses and hands-on projects.

[1043] "Information processing equipment" refers to a terminal that allows a user to interact with a computer, and primarily includes devices such as smartphones and PCs.

[1044] "Opinions" means feedback or comments provided by users, including information needed to improve or adjust the Plan.

[1045] "Economic trends" refers to current market conditions and overall economic trends, including job information and industry growth forecasts.

[1046] "Employment information" refers to information related to specific job openings and job seekers in the current job market, including employment conditions and required skills.

[1047] "Visually easy to understand" refers to a display format that allows users to intuitively understand the proposed plan, including graphical interfaces and infographics.

[1048] MODE FOR CARRYING OUT THE INVENTION

[1049] This invention relates to a system that proposes optimal career and study plans based on the abilities, educational level, work history, and goals input by a user. This system is realized mainly using a user terminal, a server, a data storage device, and various software components.

[1050] User terminal

[1051] A user terminal is a device that a user uses to access a system and input the necessary information. This mainly includes PCs, smartphones, and tablets. Users input information into a form displayed on the terminal screen.

[1052] For example, enter the following information:

[1053] Skills: Python programming

[1054] Education level: University graduate

[1055] Work Experience: 5 years of experience as a software engineer

[1056] Goal: I want to become an AI engineer

[1057] server

[1058] The server receives the information sent by the user and stores it in a data storage device. The data from the user is transmitted via a secure protocol (e.g., HTTPS). The received data is stored in a database.

[1059] Data Storage Device

[1060] Data storage is a system that organizes user information appropriately and makes it quickly accessible, using a relational database management system (RDBMS) or a NoSQL database.

[1061] Information Processing

[1062] The server retrieves the information stored in the data storage device and analyzes it using AI algorithms. These algorithms utilize generative AI models to recommend skills and learning resources needed to achieve the user's goals. Data analysis software such as Python and R is used on the server.

[1063] for example,

[1064] If a user's goal is to "become an AI engineer," the AI ​​algorithm will determine that skills like "machine learning" and "data science" are required, and will then recommend appropriate online courses and projects.

[1065] Plan Generation

[1066] Based on the analysis results of the AI ​​algorithm, the server generates a career plan and study plan tailored to each user. The plan includes specific steps and is presented in a form that the user can follow.

[1067] For example, specific plans such as "take an online data science course" or "start a machine learning project in Python" are generated.

[1068] Presenting the plan

[1069] The server sends the generated plan to the user's device, where the user can view the plan on their own device. Specifically, the plan displays "Data Science Course Links" and "Practical Project Idea List," allowing the user to access these resources.

[1070] Receive feedback and readjust

[1071] The user provides feedback on the proposed plan, for example, by inputting specific opinions such as "I'm interested in this course" or "This step is too difficult." The server receives this feedback and readjusts the plan using an AI algorithm. The adjusted plan is then sent back to the user's device, where the user can review the new proposal.

[1072] Example prompt

[1073] As a concrete example, the following prompts can be provided to a generative AI model:

[1074] "If a user sets a goal of 'I want to become an AI engineer,' please provide them with the necessary skills and a recommended learning plan."

[1075] "How do we generate the optimal learning plan for a user with Python programming skills, a college degree, and five years of software engineering experience?"

[1076] By implementing this invention, users are empowered to take concrete and effective steps towards their career goals.

[1077] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1078] Step 1:

[1079] User enters information and submits

[1080] The user enters the following information into a form on their device: ability (e.g., Python programming), level of education (e.g., university graduate), work experience (e.g., 5 years of experience as a software engineer), and goal (e.g., want to become an AI engineer). After entering the information, they press the "Submit" button, and this information is sent to the server using HTTPS.

[1081] Input: User skills, education level, work history, goals

[1082] Output: User information sent to the server

[1083] Step 2:

[1084] The server receives and stores the data

[1085] The server receives the data sent by the user and stores it in a data storage device. In the database, skill information is stored in a skill table, education level in an education table, and work history in a work history table.

[1086] Input: User information sent to the server

[1087] Output: User information stored in the database

[1088] Step 3:

[1089] The server analyzes the data

[1090] The server retrieves user information stored in the database and analyzes it using an AI algorithm. The AI ​​algorithm then uses a generative AI model to recommend skills and learning resources necessary to achieve the user's goals. For example, if the goal is to "become an AI engineer," the analysis results would include "machine learning" and "data science."

[1091] Input: User information stored in the database

[1092] Output: Recommendations for optimal skills and learning resources

[1093] Step 4:

[1094] The server generates a plan

[1095] Based on the results of the AI ​​algorithm's analysis, the server generates a personalized career and learning plan for each user, with specific steps such as "take an online data science course" or "start a machine learning project in Python."

[1096] Input: Recommendations for optimal skills and learning resources

[1097] Output: Generated career and study plans

[1098] Step 5:

[1099] The server presents the plan to the user

[1100] The server sends the generated plan to the user's device, where the user can view it and see specific links and steps in a visually understandable format. For example, "Data Science Course Links" and "Practical Project Idea List" are displayed.

[1101] Input: Generated career and study plans

[1102] Output: The plan displayed on the user's device

[1103] Step 6:

[1104] Users provide feedback and readjust

[1105] The user provides feedback on the presented plan, such as "I'm interested in this course" or "This step is too difficult." The server receives this feedback and readjusts the plan using an AI algorithm. The adjusted plan is then sent back to the user's device.

[1106] Input: User feedback

[1107] Output: Realigned career and study plans

[1108] (Application example 1)

[1109] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1110] Currently, there are systems that suggest career and learning plans, but there is a lack of systems that support payment management and fund tracking for related learning courses and services. Furthermore, the ability to adjust plans based on user feedback is insufficient, making it difficult to flexibly respond to user needs.

[1111] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1112] In this invention, the server includes: a means for a user to input skills, educational level, career history, and goals; a means for transmitting the input information to the server; a means for performing data analysis based on the stored information; a means for generating an optimal career plan and learning plan based on the analysis results; a means for managing payments for learning courses and services based on the proposed plan; and a means for providing and tracking the use of funds for achieving the career plan. This allows users to centrally manage payments for learning courses and services to implement their optimal career plan and track the use of funds. Furthermore, by readjusting the plan based on user feedback, the plan can be flexibly changed to meet needs.

[1113] "User" refers to any individual or legal entity that uses the System.

[1114] "Skills" refer to the abilities and knowledge required to perform a particular task or activity.

[1115] "Education level" refers to the educational background and learning progress of the user at an educational institution.

[1116] A "career history" is a record of a user's work history and professional experience.

[1117] "Goals" refer to the specific career or learning goals that a user is trying to achieve.

[1118] "Server" refers to an information processing device that receives and stores data from users and processes that data.

[1119] "Database" means the data structures and software systems used to manage and store User information.

[1120] "Data analysis" refers to the analytical process that the system uses to generate optimal career and study plans based on the input user information.

[1121] "Career plan" refers to the plan and specific steps a user takes to reach the career or job they are aiming for.

[1122] "Study Plan" means the learning plan and specific courses that a User takes to acquire the necessary skills toward their career goals.

[1123] "Payment" refers to the act of a user paying for a learning course or service provided.

[1124] "Funding Tracking" refers to the management and recording of funds a user has invested to achieve their career goals.

[1125] "Feedback" refers to the opinions and evaluations provided by users regarding proposed plans.

[1126] "Readjustment" refers to modifying or changing existing career or study plans based on feedback received from users.

[1127] Overall system configuration

[1128] This invention is an AI system for supporting users in achieving their career goals, and in particular has a payment management function related to career and learning plan proposals. The system includes the following main components:

[1129] User Interface

[1130] Data transmission

[1131] Data Storage

[1132] Data analysis

[1133] Plan generation and presentation

[1134] Feedback and Recalibration

[1135] Payment Management

[1136] Funds Tracking

[1137] User Interface

[1138] Users are provided with an interface to input their skills, education level, background, and goals, which can be entered through a website or mobile application.

[1139] Data Transmission and Storage

[1140] The information entered by the user is sent to the server using a secure protocol (e.g. HTTPS), and the server stores the received information in a database for efficient management.

[1141] Data analysis and plan generation

[1142] The server runs AI algorithms based on the stored information to generate optimal career and learning plans based on the user's skills, education level, background, and goals. The AI ​​models used include the Logistic Regression model.

[1143] Plan presentation and feedback

[1144] The generated plan is sent to the user's device for review, and the user can provide feedback on the plan, which the server then uses to adjust the plan.

[1145] Payment Management

[1146] Payment for the proposed course or service is managed within the system, and payment is completed by entering payment information.

[1147] Funds Tracking

[1148] It also provides a tracking function for the use of funds invested in achieving career plans, allowing users to manage their funds efficiently.

[1149] Adding specific examples to the description

[1150] For example, a user enters the information "Python programming", "college graduate", "5 years of experience as a software engineer", and "I want to become an AI engineer", and sends the following prompt to the server:

[1151] Skills: Python programming

[1152] Education level: University graduate

[1153] Experience: 5 years of experience as a software engineer

[1154] Goal: I want to become an AI engineer

[1155] This information is stored in a database, and the AI ​​model performs the necessary analysis to generate a specific career plan, such as "take an online data science course" or "start a machine learning project in Python." This plan is then presented to the user, who can then make course payments and manage their finances centrally based on the proposal.

[1156] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1157] Step 1:

[1158] Users enter their skills, education level, background, and goals.

[1159] The input information could be, for example, "Python programming," "university graduate," "5 years of experience as a software engineer," or "I want to become an AI engineer." This information is provided through a user interface (website or mobile application).

[1160] Step 2:

[1161] The user's terminal transmits the input information to the server.

[1162] This uses a secure protocol such as HTTPS.

[1163] Input data is sent and the server receives the data.

[1164] Step 3:

[1165] The server stores the received information in a database.

[1166] The data stored includes skill information, education level, career history, and goals, making it easier to manage user information on the database.

[1167] Step 4:

[1168] An AI algorithm on the server retrieves user information from the database and performs data analysis.

[1169] Specifically, it uses AI models (e.g., logistic regression) to analyze the user's skills and goals, which then triggers the creation of a career and learning plan tailored to the user.

[1170] Step 5:

[1171] The server generates a career plan and a study plan based on the analysis results.

[1172] For example, the generated plan might include "Take an online data science course" or "Start a machine learning project in Python," giving users a clear understanding of the steps involved.

[1173] Step 6:

[1174] The generated plan is sent to the user's terminal.

[1175] The user's device displays this received information in a visually easy-to-understand format, such as course links or a list of project ideas on the user interface.

[1176] Step 7:

[1177] The user reviews the generated plan and provides feedback.

[1178] The feedback includes evaluation of the plan and suggestions for improvement, etc. The feedback is sent back to the server.

[1179] Step 8:

[1180] The server readjusts the plan based on the feedback it receives.

[1181] A new, optimized plan is generated based on the user's opinions, allowing for flexible changes to the plan according to the user's needs.

[1182] Step 9:

[1183] The server manages payments for learning courses and services based on the proposed plan.

[1184] Once the user enters their payment information, the payment is completed and stored in a database, facilitating access to related courses and services.

[1185] Step 10:

[1186] The server provides usage and tracking of funds invested in achieving career plans.

[1187] Users can view the progress and usage history of their funds, which allows them to manage their funds according to plan.

[1188] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1189] This invention relates to an AI system that proposes optimal career and study plans to help users achieve their career goals. The system generates appropriate plans based on the user's skills, educational level, career history, and goals, and also has the ability to recognize the user's emotions and adjust the plans accordingly.

[1190] System configuration

[1191] The system configuration is as follows:

[1192] 1. User Interface

[1193] Users input their skills, education level, background, and goals, which are provided in the form of a website or mobile application.

[1194] 2. Data Transmission

[1195] The user's device sends the entered information to the server. The data is transmitted using a secure protocol (e.g., HTTPS).

[1196] 3. Data Storage

[1197] The server stores the received information in a database, which efficiently manages user information and allows for rapid data access.

[1198] 4. Data Analysis

[1199] The server uses the stored information to run AI algorithms that generate optimal career and study plans based on the user's skills, education level, background, and goals.

[1200] 5. Emotion Engine

[1201] It is equipped with an emotion engine that recognizes the user's emotions. The emotion engine analyzes emotions from the user's input and dialogue history.

[1202] 6. Plan generation and consideration of emotional feedback

[1203] The server takes into account the analysis results of the AI ​​algorithm and feedback from the emotion engine to generate the optimal career and study plans for the user.

[1204] For example, if a user is feeling stressed, suggestions for relaxing study methods can be included.

[1205] 7. Plan Presentation

[1206] The server sends the generated plan to the user's device, where the user can view the plan and learn the specific steps.

[1207] 8. Feedback and Recalibration

[1208] The server receives the feedback and emotional data provided by the user and readjusts the career and learning plans accordingly.

[1209] Explanation of program processing

[1210] The program processing in this system is carried out as follows.

[1211] 1. Entering and submitting information

[1212] Users input their skills, education level, background, goals, as well as emotional input (e.g., "I'm feeling stressed").

[1213] This information is sent to the server by pressing the send button.

[1214] 2. Receipt and storage of data

[1215] The server receives the information sent by the user and stores it in a database.

[1216] The information is organized for each user and recorded in the appropriate tables.

[1217] 3. Data Analysis

[1218] An AI algorithm on the server retrieves user information from the database and analyzes it.

[1219] For example, if a user's goal is to "become an AI engineer," the system will recommend "machine learning" and "data science" as necessary skills.

[1220] 4. Emotion Data Analysis

[1221] The server's emotion engine analyzes the user's emotion data and determines the user's current emotional state.

[1222] 5. Plan Generation

[1223] The server generates optimal career and study plans based on the analysis results of the AI ​​algorithm and feedback from the emotion engine.

[1224] For example, specific plans such as "take an online data science course" or "start a machine learning project in Python" are generated.

[1225] 6. Presenting the plan

[1226] The server sends the generated plan to the user's device, where it is encoded in JSON format and received by the device.

[1227] 7. User Confirms Plan

[1228] The user checks the generated plan on their own device, which displays the plan in a visually easy-to-understand format.

[1229] 8. Receive feedback and readjust

[1230] The user inputs feedback about the plan and sends it to the server. The feedback includes evaluation of the plan and requests for additions.

[1231] The server receives feedback and emotional data from users and readjusts their career and learning plans based on this.

[1232] This series of processes allows users to obtain concrete steps to effectively advance their careers. In addition, the emotion engine reduces the user's psychological burden and provides more appropriate suggestions.

[1233] The processing flow will be explained below.

[1234] Program processing flow

[1235] Step 1:

[1236] Users log in to the platform, either by creating an account if they are new users or by entering their login details if they are existing users.

[1237] Step 2:

[1238] Users input their skills, education level, career history, goals, and current emotional state. For example, they input "Python programming" as a skill, "university graduate" as an education level, "5 years of experience as a software engineer" as a career history, "I want to become an AI engineer" as a goal, and "I feel stressed" as an emotional state.

[1239] Step 3:

[1240] The device sends the entered information to the server. The data is transmitted using a secure protocol (e.g., HTTPS).

[1241] Step 4:

[1242] The server receives the information sent by the users and stores it in a database, organized by user and recorded in the appropriate tables.

[1243] Step 5:

[1244] The server retrieves the stored user information from the database and passes it to the AI ​​algorithm, which analyzes this information and generates the optimal career and study plan for the user.

[1245] Step 6:

[1246] The server's emotion engine analyzes the user's emotion data. For example, if the user is "feeling stressed," the emotion engine analyzes the data and understands the user's psychological state.

[1247] Step 7:

[1248] Based on the analysis results of the AI ​​algorithm and feedback from the emotion engine, the server generates specific career and learning plans, such as "take an online data science course and start a machine learning project in Python," as well as "suggestions for relaxing study methods."

[1249] Step 8:

[1250] The server sends the generated plan to the user's device, where it is encoded in JSON format and received by the device.

[1251] Step 9:

[1252] The user can then view the generated plan on their device. The device displays the plan in a visually easy-to-understand format. For example, the user's device displays a "Data Science course link" and a "List of ideas for practical projects."

[1253] Step 10:

[1254] The user inputs feedback about the presented plan and sends it to the server. The feedback includes an evaluation of the plan and requests for additions. For example, the user can send feedback such as "The course is too difficult."

[1255] Step 11:

[1256] The server receives feedback from the user and, together with the emotion engine data, readjusts the career and learning plans, generating new plans as needed and sending them back to the user's device.

[1257] This series of processes allows users to obtain concrete steps to effectively advance their careers. In addition, the use of an emotion engine allows for flexible responses according to the user's psychological state.

[1258] Example 2

[1259] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1260] Conventional career and study plan proposal systems not only generate plans based on the user's skills, background, and goals, but also lack the ability to adjust the plans appropriately to take the user's emotional state into account. This makes it difficult for users to effectively advance their career or study plans while reducing the stress and burden caused by their current emotional state. Furthermore, even if they receive feedback, they lack a mechanism for appropriately readjusting the plans based on that feedback.

[1261] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1262] In this invention, the server includes means for a user to input skills, educational level, career history, and goals, means for transmitting the input information to the server, means for storing the information received by the server in a database, means for performing data analysis based on the stored information, means for generating optimal career plans and study plans based on the analysis results, means for receiving and analyzing user emotional data, means for adjusting the career plans and study plans based on the emotional data, means for transmitting the generated plans to the user's terminal, means for the user to confirm the transmitted plans, means for transmitting user feedback to the server, and means for readjusting the plans based on the feedback received by the server. This makes it possible to provide optimal career plans and study plans taking into account the user's emotional state, and to readjust the plans as necessary based on the user's feedback and emotional data.

[1263] "User" refers to an individual who uses this system to obtain a career plan and a study plan.

[1264] "Skills" refer to specific knowledge or techniques that a user possesses.

[1265] "Education level" refers to the user's educational background, such as the highest level of education and the degree obtained.

[1266] "Career" refers to the history of the jobs and tasks that a user has experienced.

[1267] "Goals" refer to the career objectives or achievements that a user wants to achieve.

[1268] "Terminal" refers to the electronic device used by a user to enter information and view plans.

[1269] "Server" refers to a central system that receives, stores, and analyzes user information, generates plans, and sends them to terminals.

[1270] "Database" refers to a data storage device for efficiently storing and managing user information and plans.

[1271] "Data analysis" refers to the process of deriving the optimal plan based on collected user information.

[1272] A "career plan" refers to the specific steps or plans a user takes to achieve their desired career goals.

[1273] A "learning plan" refers to a specific plan for a user to learn the knowledge and skills they need to acquire in order to achieve their goals.

[1274] "Emotional data" refers to information that indicates a user's emotional state, such as stress, happiness, or anxiety.

[1275] "Feedback" refers to the evaluations and comments that users make on proposed plans.

[1276] "Recalibration" refers to the process of revising and re-optimizing a plan based on user feedback and sentiment data.

[1277] "Market trends" refers to information that indicates the situation based on current economic conditions and industry trends.

[1278] "Job information" refers to information about job content and employment conditions published by companies and organizations.

[1279] "Visually easy to understand" refers to a format that is displayed graphically so that users can easily grasp the content.

[1280] This invention relates to an AI system that proposes optimal career and study plans to help users achieve their career goals. The system generates appropriate plans based on the user's skills, educational level, career history, and goals, and also has the ability to recognize the user's emotions and adjust the plans accordingly.

[1281] System configuration

[1282] 1. User Interface

[1283] Users enter information about their skills, education level, background, goals, and emotions using forms on websites and mobile applications.

[1284] 2. Data Transmission

[1285] The terminal transmits the entered information to the server using a secure protocol (e.g., HTTPS).

[1286] 3. Data Storage

[1287] The server stores the received information in a database, which allows efficient management and rapid access to large amounts of data.

[1288] 4. Data Analysis

[1289] The server runs AI algorithms based on the stored information, analyzing the user's skills, education level, background, and goals to generate optimal career and learning plans.

[1290] 5. Emotion Engine

[1291] The server uses an emotion engine to analyze emotion data from user input and dialogue history, thereby recognizing the user's emotional state and reflecting it in the career plan.

[1292] 6. Plan generation and consideration of emotional feedback

[1293] The server combines the analysis results of the AI ​​algorithm with feedback from the emotion engine to generate optimal career and study plans for the user. For example, if the user is feeling stressed, the server can include suggestions for relaxing study methods.

[1294] 7. Plan Presentation

[1295] The server encodes the generated plan in JSON format or similar and sends it to the device, which then displays the received plan in a visually easy-to-understand format.

[1296] 8. Feedback and Recalibration

[1297] The user inputs feedback on the received plan and sends it to the server, which then readjusts the career and learning plans based on this feedback and emotional data.

[1298] Specific examples

[1299] For example, consider a user who has a goal of becoming an AI engineer. The user inputs "Python" and "Basic Mathematics" as their current skills, "University Graduate" as their education level, "Data Analyst" as their career, and "Feeling Stressed" as their emotional state.

[1300] Based on this information, the server analyzes that having skills in "machine learning" and "data science" is important for becoming an AI engineer. In addition, the emotion engine recognizes that the user is feeling stressed and suggests a learning plan that includes "taking an online course" and "relaxation sessions" as a way to relax.

[1301] Prompt Sentence Examples

[1302] "Please suggest a career plan for becoming an AI engineer. Your current skills are basic Python and math, you have graduated from university, and you are working as a data analyst. Please also consider the stress you are experiencing."

[1303] By inputting these prompts into a generative AI model, a career and learning plan optimized for the user's needs and emotional state is provided. Through this process, users are provided with concrete steps to effectively advance their careers, helping them achieve their goals while reducing emotional burden.

[1304] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1305] Step 1:

[1306] Users enter information about their skills, education level, career history, goals, and emotions.

[1307] Input: User skills, education level, background, goals, emotions (e.g., "Python," "College graduate," "Data analyst," "I want to be an AI engineer," "I'm stressed").

[1308] What happens: A user fills out a form on a website or mobile application.

[1309] Output: The input information is encoded in JSON format.

[1310] Step 2:

[1311] The terminal transmits the entered information to the server using a secure protocol (e.g., HTTPS).

[1312] Input: User information encoded in JSON format.

[1313] Operation: After the send button is pressed, the device sends the data to the server using HTTPS.

[1314] Output: The encoded JSON data is sent to the server.

[1315] Step 3:

[1316] The server stores the received information in a database.

[1317] Input: User information encoded in JSON format.

[1318] How it works: The server parses the information and stores it in the appropriate tables in the database. Each item (skills, education level, career history, goals, emotional data) is associated with the user ID.

[1319] Output: The user information is saved in the database.

[1320] Step 4:

[1321] The server runs AI algorithms based on the stored information and performs data analysis.

[1322] Input: User's skills, education level, background, and goals retrieved from the database.

[1323] How it works: AI algorithms analyze this information to identify the best skill sets and learning content for your goals.

[1324] Output: Specific career and learning plans, such as "take a machine learning course" or "study data science."

[1325] Step 5:

[1326] The server receives and analyzes the user's emotion data.

[1327] Input: User emotion data retrieved from the database.

[1328] How it works: The emotion engine analyzes emotion data and identifies emotional states such as "feeling stressed."

[1329] Output: The user's emotional state (e.g., stress, happiness, anxiety).

[1330] Step 6:

[1331] The server integrates the analysis results of the AI ​​algorithm with feedback from the emotion engine to generate optimal career and learning plans.

[1332] Input: Analysis results of AI algorithm, feedback from emotion engine.

[1333] How it works: The server integrates these data and generates a plan that takes into account the user's emotional state, for example, "a study plan that includes relaxation sessions to reduce stress."

[1334] Output: Optimized career and study plans.

[1335] Step 7:

[1336] The server encodes the generated plan in JSON format and sends it to the terminal.

[1337] Input: Generated career and study plans.

[1338] How it works: The server encodes the plan into JSON format and sends it to the device.

[1339] Output: The encoded JSON data.

[1340] Step 8:

[1341] The terminal decodes the received JSON data and displays it in a visually easy-to-understand format.

[1342] Input: JSON data received from the server.

[1343] How it works: The device decodes the data and displays it in a visually understandable format such as a timeline or list. For example, "Online courses taken" or "Relaxation sessions attended."

[1344] Output: Career and study plans in a user-readable format.

[1345] Step 9:

[1346] The user inputs feedback on the plan and sends it to the server.

[1347] Input: Your rating and comments on the plan (e.g., "There's too much to learn").

[1348] How it works: The user enters their feedback and presses the submit button to send it to the server.

[1349] Output: Feedback information is sent to the server.

[1350] Step 10:

[1351] The server readjusts career and learning plans based on the feedback received.

[1352] Input: User feedback and sentiment data.

[1353] How it works: Based on feedback and sentiment data, the AI ​​algorithm is re-run to optimize the plan, for example by reducing learnings and splitting the progress schedule.

[1354] Output: A realigned career and study plan.

[1355] This series of processing flows allows users to obtain optimal career and study plans while taking into consideration their own emotional state.

[1356] (Application example 2)

[1357] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1358] Previous career and study plan generation systems did not take into account the user's emotional state or psychological burden, and were not specialized for in-store counseling support. As a result, they were unable to make optimal suggestions based on the user's emotional state, making it difficult to propose career plans that would minimize stress for users. Furthermore, because they did not support in-store counseling support, it was difficult to provide consistent service to users in-store.

[1359] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing the customer's emotions and adjusting the plan based on these emotions, means for inputting the user's skills, educational level, work history, and goals and generating optimal career and study plans based on this information, and means for transmitting the generated plans to the user's terminal and readjusting the plans based on the user's opinions. This makes it possible to propose optimal career and study plans based on the user's emotional state, and also enables counseling support in physical stores and stress reduction for users.

[1360] "User" refers to a person who uses the system.

[1361] "Skills" refers to the abilities and knowledge related to a particular task or occupation.

[1362] "Education level" refers to the level of education or academic background of the user.

[1363] "Work history" refers to the occupations and work experiences that a user has had in the past.

[1364] "Goals" refers to the career or academic goals that the user is trying to achieve in the future.

[1365] "Input means" refers to the method or device by which a user provides information about himself or herself to the system.

[1366] "Server" refers to a computer system that processes, stores, analyzes, and transmits information received from users.

[1367] "Data Storage Device" means a database or other storage device for storing user-provided information.

[1368] "Information analysis" refers to the process by which the server utilizes data received from the user to generate specific results or recommendations.

[1369] A "career plan" refers to a plan that includes procedures or steps to achieve a desired career for a user.

[1370] A "learning plan" refers to a plan for a user to acquire the knowledge and skills necessary to achieve a goal.

[1371] "Emotion analysis" refers to recognizing a user's emotions and psychological state and analyzing that information.

[1372] "Opinions" refer to feedback and requests that users provide regarding the generated plan.

[1373] "Adjustment means" refers to methods or devices that modify or improve the plan based on the user's opinions or emotional state.

[1374] "Terminal" refers to the computer or smart device that a user uses to interact with the system.

[1375] This invention relates to an AI system that proposes optimal career and study plans for users to achieve their career goals. The system generates plans based on the user's skills, educational level, work history, and goals, and also has the ability to adjust the plans by recognizing the user's emotions.

[1376] System configuration

[1377] 1. User Interface

[1378] Users input their skills, educational level, work history, and goals using devices such as smartphones or tablets. The system is intended to be used as a career counseling support tool in brick-and-mortar stores.

[1379] 2. Data Transmission

[1380] The user terminal sends the entered information to the server using a secure protocol (e.g., HTTPS), which helps protect privacy.

[1381] 3. Data Storage

[1382] The server stores the received information in a database (e.g., MySQL, PostgreSQL). Each user's information is managed efficiently and data access is rapid.

[1383] 4. Data Analysis

[1384] The server runs AI algorithms based on the stored information to generate optimal career and learning plans based on the user's skills, educational level, work history, and goals. The analysis uses AI models (e.g., machine learning libraries TensorFlow and PyTorch).

[1385] 5. Emotion analysis

[1386] The server uses an emotion engine (e.g., NLTK, TextBlob) that recognizes emotions from user input and dialogue history, thereby determining the user's psychological state and reflecting the feedback in the plan generation.

[1387] 6. Plan generation and consideration of emotional feedback

[1388] The server generates optimal career and study plans for users based on the analysis results of the AI ​​algorithm and feedback from the emotion engine. For example, if a user is feeling stressed, it will suggest relaxation methods for studying (e.g., using a meditation app or engaging in fitness activities).

[1389] 7. Presenting the plan

[1390] The server sends the generated plan to the user's terminal, where the plan is displayed in a visually easy-to-understand format.

[1391] 8. Feedback and Recalibration

[1392] The server receives feedback and emotional data provided by users and adjusts their career and learning plans accordingly, enabling the system to continuously provide optimal suggestions tailored to each individual user.

[1393] Specific examples

[1394] Specific hardware examples

[1395] Smartphones and tablets (e.g. iPhone, iPad, Samsung Galaxy)

[1396] Specific software examples

[1397] Frameworks used for REST API development (e.g., Flask, Django)

[1398] Simple sentiment analysis library (e.g. NLTK, TextBlob)

[1399] Example prompts to input to the generative AI model

[1400] What are your career goals? Tell us about your current skills, education level, and background. Also, describe your current emotional state.

[1401] This system is specialized for supporting career counseling in brick-and-mortar stores, and is able to propose optimal career plans that take into account the user's emotions. In this way, it is possible to provide users with effective career counseling with less stress.

[1402] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1403] Step 1:

[1404] The user enters information about themselves into the device, such as their skills, educational level, work history, goals, and emotional state (e.g., "I'm feeling stressed"). This information is collected through the app's user interface. The input data is structured in a standard format, such as JSON.

[1405] Step 2:

[1406] The terminal sends the entered information to the server. The data sent is encrypted using a secure protocol (e.g. HTTPS). The server stores the received data in a database. The database has a table for each user, allowing for efficient data reference.

[1407] Step 3:

[1408] The server analyzes the information stored in the data storage. Specifically, it uses AI algorithms to generate career and study plans suited to the user's skills, educational level, work history, and goals. The AI ​​algorithms used utilize machine learning frameworks (e.g., TensorFlow, PyTorch).

[1409] Step 4:

[1410] The server analyzes the user's emotions using a sentiment analysis engine. It recognizes emotions based on the input text and dialogue history. The sentiment analysis engine used uses a natural language processing library (e.g., NLTK, TextBlob).

[1411] Step 5:

[1412] The server generates optimal career and study plans based on the results of the AI ​​model analysis and feedback from emotion analysis. For example, if a user is feeling stressed, it will provide a study plan incorporating relaxation techniques. The generated plans are encoded in JSON format or similar.

[1413] Step 6:

[1414] The server sends the generated career plan and study plan to the terminal, which displays the received data in a visually easy-to-understand format (e.g., charts and lists).

[1415] Step 7:

[1416] The user checks the provided career plan and learning plan and inputs feedback. The user also inputs their evaluation of the plan and any additional requests. The feedback data is then sent back to the server.

[1417] Step 8:

[1418] The server analyzes the user's feedback and adjusts the career and learning plans as needed. This can be done using machine learning algorithms or rule-based engines. The adjusted plans are then sent back to the user's device, completing the feedback loop for the entire system.

[1419] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1420] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1421] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1422] [Fourth embodiment]

[1423] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1424] 7, a 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.

[1425] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1426] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1427] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1428] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1429] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1430] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1431] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1432] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1433] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1434] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1435] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1436] This invention relates to an AI system that proposes optimal career and study plans to help users achieve their career goals. This system generates and presents appropriate plans to users based on their skills, educational level, career history, and goals.

[1437] System configuration

[1438] The system configuration is as follows:

[1439] 1. User Interface

[1440] Users input their skills, education level, background, and goals, which are provided in the form of a website or mobile application.

[1441] 2. Data Transmission

[1442] The user's device sends the entered information to the server. The data is sent using a secure protocol (e.g., HTTPS).

[1443] 3. Data Storage

[1444] The server stores the received information in a database, which efficiently manages user information and allows for rapid data access.

[1445] 4. Data Analysis

[1446] The server uses the stored information to run AI algorithms that generate optimal career and study plans based on the user's skills, education level, background, and goals.

[1447] 5. Plan Generation and Presentation

[1448] The server sends the generated plan to the user's device, where the user can check the plan and learn the specific steps.

[1449] 6. Feedback and Recalibration

[1450] The server receives the feedback provided by the user and readjusts the career and study plans accordingly.

[1451] Explanation of program processing

[1452] The program processing in this system is carried out as follows.

[1453] 1. Entering and submitting information

[1454] The user inputs their skills, educational level, career history, and goals, and sends the information to the server by pressing the send button.

[1455] For example, a user enters and submits information such as "Python programming," "university graduate," "5 years of experience as a software engineer," and "I want to become an AI engineer."

[1456] 2. Receipt and storage of data

[1457] The server receives the information sent by the user and stores the information in a database.

[1458] For example, information about each user is stored in a corresponding table (eg, a skills table, an education table, a career table) in the database.

[1459] 3. Data Analysis

[1460] An AI algorithm on the server retrieves user information from the database and analyzes it.

[1461] For example, if a user's goal is to "become an AI engineer," an AI algorithm will recommend "machine learning" and "data science" as necessary skills.

[1462] 4. Plan Generation

[1463] The server generates optimal career and study plans based on the analysis results of the AI ​​algorithm.

[1464] For example, specific plans such as "take an online data science course" or "start a machine learning project in Python" are generated.

[1465] 5. Presenting the plan

[1466] The server sends the generated plan to the user's terminal, where the user can view the plan.

[1467] For example, a "data science course link" or a "list of practical project ideas" will be displayed on the user's device.

[1468] 6. Receive feedback and readjust

[1469] The user sends feedback about the plan to the server, which then adjusts the career and learning plan based on the feedback.

[1470] For example, if a user submits feedback indicating interest in a particular course, the server generates a new plan accordingly.

[1471] This process effectively enables users to take concrete steps towards their career goals.

[1472] The processing flow will be explained below.

[1473] Program processing flow

[1474] Step 1:

[1475] Users log in to the platform, either by creating an account if they are new users or by entering their login details if they are existing users.

[1476] Step 2:

[1477] Users input their skills, education level, background, and goals, clarifying their current status and future goals.

[1478] Step 3:

[1479] The device sends the entered information to the server. The data is transmitted using a secure protocol (e.g., HTTPS).

[1480] Step 4:

[1481] The server receives the information sent by the users and stores it in a database, organized by user and recorded in the appropriate tables.

[1482] Step 5:

[1483] The server retrieves the stored user information from the database and passes it to the AI ​​algorithm, which analyzes this information and generates the optimal career and study plan for the user.

[1484] Step 6:

[1485] Based on the results of the AI ​​algorithm's analysis, the server generates a specific career and learning plan, such as "take an online data science course and start a machine learning project in Python."

[1486] Step 7:

[1487] The server sends the generated plan to the user's device, where it is encoded in JSON format and received by the device.

[1488] Step 8:

[1489] The user checks the generated plan on their own device, which displays the plan in a visually easy-to-understand format.

[1490] Step 9:

[1491] The user inputs feedback about the proposed plan and sends it to the server. The feedback includes evaluation of the plan and requests for additions.

[1492] Step 10:

[1493] The server receives feedback from the user and adjusts the career and learning plans based on this feedback, generating new plans as needed and sending them back to the user's device.

[1494] This process provides users with concrete steps to effectively advance their careers.

[1495] Example 1

[1496] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1497] Conventional career and learning plan proposal systems have struggled to generate optimal plans based on a user's individual skills and goals. Furthermore, they lacked a mechanism for appropriately reflecting and adjusting user feedback on the generated plans, making it difficult to provide plans that maximize the user's benefits. Furthermore, generating plans that take into account economic trends and job information, and providing displays that are visually easy to understand, were also issues.

[1498] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1499] In this invention, the server includes: means for a user to input their abilities, educational level, work history, and goals; means for transmitting the input data to a computer; means for the computer to store the received data in a data storage device; means for processing the stored data; means for generating an optimal career plan and study plan based on the results of the information processing; means for the user to confirm the transmitted plan; means for the user to transmit the user's opinions to the computer; means for the computer to readjust the plan based on the received opinions; means for collecting economic trends and employment information and generating the user's career plan and study plan based thereon; and means for the user's information processing device to display the plan in a visually easy-to-understand format. This enables the provision of an optimal career and study plan based on the user's individual skills and goals, and also makes it easy to readjust the plan by reflecting the user's feedback. As a result, a plan that is most effective for the user can be provided.

[1500] "Ability" refers to the level of a user's technology and knowledge, including specific skills and specialized knowledge.

[1501] "Educational level" refers to the user's educational background and level of education, including classifications such as junior high school graduate, high school graduate, and university graduate.

[1502] "Work experience" refers to the occupations, industries, positions, etc. that a user has had up to now, including specific years of employment and roles.

[1503] "Goals" refer to the specific objectives and visions that a user wants to achieve in relation to their occupation or career, and include long-term goals and short-term goals.

[1504] "Computer" refers to a central control unit that processes, stores, and analyzes information sent by users, and primarily functions as a server.

[1505] "Data storage device" refers to a device for storing user information received by a computer, including a database or other storage medium.

[1506] "Information processing" refers to a series of processes that analyze and calculate stored data to derive meaningful results, and primarily involves analysis using AI algorithms.

[1507] A "career plan" refers to specific career paths and steps proposed based on the user's career goals, including methods for acquiring necessary skills and education.

[1508] A "learning plan" refers to a specific learning method or course that a user uses to acquire new skills or knowledge, including online courses and hands-on projects.

[1509] "Information processing equipment" refers to a terminal that allows a user to interact with a computer, and primarily includes devices such as smartphones and PCs.

[1510] "Opinions" means feedback or comments provided by users, including information needed to improve or adjust the Plan.

[1511] "Economic trends" refers to current market conditions and overall economic trends, including job information and industry growth forecasts.

[1512] "Employment information" refers to information related to specific job openings and job seekers in the current job market, including employment conditions and required skills.

[1513] "Visually easy to understand" refers to a display format that allows users to intuitively understand the proposed plan, including graphical interfaces and infographics.

[1514] MODE FOR CARRYING OUT THE INVENTION

[1515] This invention relates to a system that proposes optimal career and study plans based on the abilities, educational level, work history, and goals input by a user. This system is realized mainly using a user terminal, a server, a data storage device, and various software components.

[1516] User terminal

[1517] A user terminal is a device that a user uses to access a system and input the necessary information. This mainly includes PCs, smartphones, and tablets. Users input information into a form displayed on the terminal screen.

[1518] For example, enter the following information:

[1519] Skills: Python programming

[1520] Education level: University graduate

[1521] Work Experience: 5 years of experience as a software engineer

[1522] Goal: I want to become an AI engineer

[1523] server

[1524] The server receives the information sent by the user and stores it in a data storage device. The data from the user is transmitted via a secure protocol (e.g., HTTPS). The received data is stored in a database.

[1525] Data Storage Device

[1526] Data storage is a system that organizes user information appropriately and makes it quickly accessible, using a relational database management system (RDBMS) or a NoSQL database.

[1527] Information Processing

[1528] The server retrieves the information stored in the data storage device and analyzes it using AI algorithms. These algorithms utilize generative AI models to recommend skills and learning resources needed to achieve the user's goals. Data analysis software such as Python and R is used on the server.

[1529] for example,

[1530] If a user's goal is to "become an AI engineer," the AI ​​algorithm will determine that skills like "machine learning" and "data science" are required, and will then recommend appropriate online courses and projects.

[1531] Plan Generation

[1532] Based on the analysis results of the AI ​​algorithm, the server generates a career plan and study plan tailored to each user. The plan includes specific steps and is presented in a form that the user can follow.

[1533] For example, specific plans such as "take an online data science course" or "start a machine learning project in Python" are generated.

[1534] Presenting the plan

[1535] The server sends the generated plan to the user's device, where the user can view the plan on their own device. Specifically, the plan displays "Data Science Course Links" and "Practical Project Idea List," allowing the user to access these resources.

[1536] Receive feedback and readjust

[1537] The user provides feedback on the proposed plan, for example, by inputting specific opinions such as "I'm interested in this course" or "This step is too difficult." The server receives this feedback and readjusts the plan using an AI algorithm. The adjusted plan is then sent back to the user's device, where the user can review the new proposal.

[1538] Example prompt

[1539] As a concrete example, the following prompts can be provided to a generative AI model:

[1540] "If a user sets a goal of 'I want to become an AI engineer,' please provide them with the necessary skills and a recommended learning plan."

[1541] "How do we generate the optimal learning plan for a user with Python programming skills, a college degree, and five years of software engineering experience?"

[1542] By implementing this invention, users are empowered to take concrete and effective steps towards their career goals.

[1543] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1544] Step 1:

[1545] User enters information and submits

[1546] The user enters the following information into a form on their device: ability (e.g., Python programming), level of education (e.g., university graduate), work experience (e.g., 5 years of experience as a software engineer), and goal (e.g., want to become an AI engineer). After entering the information, they press the "Submit" button, and this information is sent to the server using HTTPS.

[1547] Input: User skills, education level, work history, goals

[1548] Output: User information sent to the server

[1549] Step 2:

[1550] The server receives and stores the data

[1551] The server receives the data sent by the user and stores it in a data storage device. In the database, skill information is stored in a skill table, education level in an education table, and work history in a work history table.

[1552] Input: User information sent to the server

[1553] Output: User information stored in the database

[1554] Step 3:

[1555] The server analyzes the data

[1556] The server retrieves user information stored in the database and analyzes it using an AI algorithm. The AI ​​algorithm then uses a generative AI model to recommend skills and learning resources necessary to achieve the user's goals. For example, if the goal is to "become an AI engineer," the analysis results would include "machine learning" and "data science."

[1557] Input: User information stored in the database

[1558] Output: Recommendations for optimal skills and learning resources

[1559] Step 4:

[1560] The server generates a plan

[1561] Based on the results of the AI ​​algorithm's analysis, the server generates a personalized career and learning plan for each user, with specific steps such as "take an online data science course" or "start a machine learning project in Python."

[1562] Input: Recommendations for optimal skills and learning resources

[1563] Output: Generated career and study plans

[1564] Step 5:

[1565] The server presents the plan to the user

[1566] The server sends the generated plan to the user's device, where the user can view it and see specific links and steps in a visually understandable format. For example, "Data Science Course Links" and "Practical Project Idea List" are displayed.

[1567] Input: Generated career and study plans

[1568] Output: The plan displayed on the user's device

[1569] Step 6:

[1570] Users provide feedback and readjust

[1571] The user provides feedback on the presented plan, such as "I'm interested in this course" or "This step is too difficult." The server receives this feedback and readjusts the plan using an AI algorithm. The adjusted plan is then sent back to the user's device.

[1572] Input: User feedback

[1573] Output: Realigned career and study plans

[1574] (Application example 1)

[1575] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1576] Currently, there are systems that suggest career and learning plans, but there is a lack of systems that support payment management and fund tracking for related learning courses and services. Furthermore, the ability to adjust plans based on user feedback is insufficient, making it difficult to flexibly respond to user needs.

[1577] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1578] In this invention, the server includes: a means for a user to input skills, educational level, career history, and goals; a means for transmitting the input information to the server; a means for performing data analysis based on the stored information; a means for generating an optimal career plan and learning plan based on the analysis results; a means for managing payments for learning courses and services based on the proposed plan; and a means for providing and tracking the use of funds for achieving the career plan. This allows users to centrally manage payments for learning courses and services to implement their optimal career plan and track the use of funds. Furthermore, by readjusting the plan based on user feedback, the plan can be flexibly changed to meet needs.

[1579] "User" refers to any individual or legal entity that uses the System.

[1580] "Skills" refer to the abilities and knowledge required to perform a particular task or activity.

[1581] "Education level" refers to the educational background and learning progress of the user at an educational institution.

[1582] A "career history" is a record of a user's work history and professional experience.

[1583] "Goals" refer to the specific career or learning goals that a user is trying to achieve.

[1584] "Server" refers to an information processing device that receives and stores data from users and processes that data.

[1585] "Database" means the data structures and software systems used to manage and store User information.

[1586] "Data analysis" refers to the analytical process that the system uses to generate optimal career and study plans based on the input user information.

[1587] "Career plan" refers to the plan and specific steps a user takes to reach the career or job they are aiming for.

[1588] "Study Plan" means the learning plan and specific courses that a User takes to acquire the necessary skills toward their career goals.

[1589] "Payment" refers to the act of a user paying for a learning course or service provided.

[1590] "Funding Tracking" refers to the management and recording of funds a user has invested to achieve their career goals.

[1591] "Feedback" refers to the opinions and evaluations provided by users regarding proposed plans.

[1592] "Readjustment" refers to modifying or changing existing career or study plans based on feedback received from users.

[1593] Overall system configuration

[1594] This invention is an AI system for supporting users in achieving their career goals, and in particular has a payment management function related to career and learning plan proposals. The system includes the following main components:

[1595] User Interface

[1596] Data transmission

[1597] Data Storage

[1598] Data analysis

[1599] Plan generation and presentation

[1600] Feedback and Recalibration

[1601] Payment Management

[1602] Funds Tracking

[1603] User Interface

[1604] Users are provided with an interface to input their skills, education level, background, and goals, which can be entered through a website or mobile application.

[1605] Data Transmission and Storage

[1606] The information entered by the user is sent to the server using a secure protocol (e.g. HTTPS), and the server stores the received information in a database for efficient management.

[1607] Data analysis and plan generation

[1608] The server runs AI algorithms based on the stored information to generate optimal career and learning plans based on the user's skills, education level, background, and goals. The AI ​​models used include the Logistic Regression model.

[1609] Plan presentation and feedback

[1610] The generated plan is sent to the user's device for review, and the user can provide feedback on the plan, which the server then uses to adjust the plan.

[1611] Payment Management

[1612] Payment for the proposed course or service is managed within the system, and payment is completed by entering payment information.

[1613] Funds Tracking

[1614] It also provides a tracking function for the use of funds invested in achieving career plans, allowing users to manage their funds efficiently.

[1615] Adding specific examples to the description

[1616] For example, a user enters the information "Python programming", "college graduate", "5 years of experience as a software engineer", and "I want to become an AI engineer", and sends the following prompt to the server:

[1617] Skills: Python programming

[1618] Education level: University graduate

[1619] Experience: 5 years of experience as a software engineer

[1620] Goal: I want to become an AI engineer

[1621] This information is stored in a database, and the AI ​​model performs the necessary analysis to generate a specific career plan, such as "take an online data science course" or "start a machine learning project in Python." This plan is then presented to the user, who can then make course payments and manage their finances centrally based on the proposal.

[1622] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1623] Step 1:

[1624] Users enter their skills, education level, background, and goals.

[1625] The input information could be, for example, "Python programming," "university graduate," "5 years of experience as a software engineer," or "I want to become an AI engineer." This information is provided through a user interface (website or mobile application).

[1626] Step 2:

[1627] The user's terminal transmits the input information to the server.

[1628] This uses a secure protocol such as HTTPS.

[1629] Input data is sent and the server receives the data.

[1630] Step 3:

[1631] The server stores the received information in a database.

[1632] The data stored includes skill information, education level, career history, and goals, making it easier to manage user information on the database.

[1633] Step 4:

[1634] An AI algorithm on the server retrieves user information from the database and performs data analysis.

[1635] Specifically, it uses AI models (e.g., logistic regression) to analyze the user's skills and goals, which then triggers the creation of a career and learning plan tailored to the user.

[1636] Step 5:

[1637] The server generates a career plan and a study plan based on the analysis results.

[1638] For example, the generated plan might include "Take an online data science course" or "Start a machine learning project in Python," giving users a clear understanding of the steps involved.

[1639] Step 6:

[1640] The generated plan is sent to the user's terminal.

[1641] The user's device displays this received information in a visually easy-to-understand format, such as course links or a list of project ideas on the user interface.

[1642] Step 7:

[1643] The user reviews the generated plan and provides feedback.

[1644] The feedback includes evaluation of the plan and suggestions for improvement, etc. The feedback is sent back to the server.

[1645] Step 8:

[1646] The server readjusts the plan based on the feedback it receives.

[1647] A new, optimized plan is generated based on the user's opinions, allowing for flexible changes to the plan according to the user's needs.

[1648] Step 9:

[1649] The server manages payments for learning courses and services based on the proposed plan.

[1650] Once the user enters their payment information, the payment is completed and stored in a database, facilitating access to related courses and services.

[1651] Step 10:

[1652] The server provides usage and tracking of funds invested in achieving career plans.

[1653] Users can view the progress and usage history of their funds, which allows them to manage their funds according to plan.

[1654] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1655] This invention relates to an AI system that proposes optimal career and study plans to help users achieve their career goals. The system generates appropriate plans based on the user's skills, educational level, career history, and goals, and also has the ability to recognize the user's emotions and adjust the plans accordingly.

[1656] System configuration

[1657] The system configuration is as follows:

[1658] 1. User Interface

[1659] Users input their skills, education level, background, and goals, which are provided in the form of a website or mobile application.

[1660] 2. Data Transmission

[1661] The user's device sends the entered information to the server. The data is transmitted using a secure protocol (e.g., HTTPS).

[1662] 3. Data Storage

[1663] The server stores the received information in a database, which efficiently manages user information and allows for rapid data access.

[1664] 4. Data Analysis

[1665] The server uses the stored information to run AI algorithms that generate optimal career and study plans based on the user's skills, education level, background, and goals.

[1666] 5. Emotion Engine

[1667] It is equipped with an emotion engine that recognizes the user's emotions. The emotion engine analyzes emotions from the user's input and dialogue history.

[1668] 6. Plan generation and consideration of emotional feedback

[1669] The server takes into account the analysis results of the AI ​​algorithm and feedback from the emotion engine to generate the optimal career and study plans for the user.

[1670] For example, if a user is feeling stressed, suggestions for relaxing study methods can be included.

[1671] 7. Plan Presentation

[1672] The server sends the generated plan to the user's device, where the user can view the plan and learn the specific steps.

[1673] 8. Feedback and Recalibration

[1674] The server receives the feedback and emotional data provided by the user and readjusts the career and learning plans accordingly.

[1675] Explanation of program processing

[1676] The program processing in this system is carried out as follows.

[1677] 1. Entering and submitting information

[1678] Users input their skills, education level, background, goals, as well as emotional input (e.g., "I'm feeling stressed").

[1679] This information is sent to the server by pressing the send button.

[1680] 2. Receipt and storage of data

[1681] The server receives the information sent by the user and stores it in a database.

[1682] The information is organized for each user and recorded in the appropriate tables.

[1683] 3. Data Analysis

[1684] An AI algorithm on the server retrieves user information from the database and analyzes it.

[1685] For example, if a user's goal is to "become an AI engineer," the system will recommend "machine learning" and "data science" as necessary skills.

[1686] 4. Emotion Data Analysis

[1687] The server's emotion engine analyzes the user's emotion data and determines the user's current emotional state.

[1688] 5. Plan Generation

[1689] The server generates optimal career and study plans based on the analysis results of the AI ​​algorithm and feedback from the emotion engine.

[1690] For example, specific plans such as "take an online data science course" or "start a machine learning project in Python" are generated.

[1691] 6. Presenting the plan

[1692] The server sends the generated plan to the user's device, where it is encoded in JSON format and received by the device.

[1693] 7. User Confirms Plan

[1694] The user checks the generated plan on their own device, which displays the plan in a visually easy-to-understand format.

[1695] 8. Receive feedback and readjust

[1696] The user inputs feedback about the plan and sends it to the server. The feedback includes evaluation of the plan and requests for additions.

[1697] The server receives feedback and emotional data from users and readjusts their career and learning plans based on this.

[1698] This series of processes allows users to obtain concrete steps to effectively advance their careers. In addition, the emotion engine reduces the user's psychological burden and provides more appropriate suggestions.

[1699] The processing flow will be explained below.

[1700] Program processing flow

[1701] Step 1:

[1702] Users log in to the platform, either by creating an account if they are new users or by entering their login details if they are existing users.

[1703] Step 2:

[1704] Users input their skills, education level, career history, goals, and current emotional state. For example, they input "Python programming" as a skill, "university graduate" as an education level, "5 years of experience as a software engineer" as a career history, "I want to become an AI engineer" as a goal, and "I feel stressed" as an emotional state.

[1705] Step 3:

[1706] The device sends the entered information to the server. The data is transmitted using a secure protocol (e.g., HTTPS).

[1707] Step 4:

[1708] The server receives the information sent by the users and stores it in a database, organized by user and recorded in the appropriate tables.

[1709] Step 5:

[1710] The server retrieves the stored user information from the database and passes it to the AI ​​algorithm, which analyzes this information and generates the optimal career and study plan for the user.

[1711] Step 6:

[1712] The server's emotion engine analyzes the user's emotion data. For example, if the user is "feeling stressed," the emotion engine analyzes the data and understands the user's psychological state.

[1713] Step 7:

[1714] Based on the analysis results of the AI ​​algorithm and feedback from the emotion engine, the server generates specific career and learning plans, such as "take an online data science course and start a machine learning project in Python," as well as "suggestions for relaxing study methods."

[1715] Step 8:

[1716] The server sends the generated plan to the user's device, where it is encoded in JSON format and received by the device.

[1717] Step 9:

[1718] The user can then view the generated plan on their device. The device displays the plan in a visually easy-to-understand format. For example, the user's device displays a "Data Science course link" and a "List of ideas for practical projects."

[1719] Step 10:

[1720] The user inputs feedback about the presented plan and sends it to the server. The feedback includes an evaluation of the plan and requests for additions. For example, the user can send feedback such as "The course is too difficult."

[1721] Step 11:

[1722] The server receives feedback from the user and, together with the emotion engine data, readjusts the career and learning plans, generating new plans as needed and sending them back to the user's device.

[1723] This series of processes allows users to obtain concrete steps to effectively advance their careers. In addition, the use of an emotion engine allows for flexible responses according to the user's psychological state.

[1724] Example 2

[1725] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1726] Conventional career and study plan proposal systems not only generate plans based on the user's skills, background, and goals, but also lack the ability to adjust the plans appropriately to take the user's emotional state into account. This makes it difficult for users to effectively advance their career or study plans while reducing the stress and burden caused by their current emotional state. Furthermore, even if they receive feedback, they lack a mechanism for appropriately readjusting the plans based on that feedback.

[1727] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1728] In this invention, the server includes means for a user to input skills, educational level, career history, and goals, means for transmitting the input information to the server, means for storing the information received by the server in a database, means for performing data analysis based on the stored information, means for generating optimal career plans and study plans based on the analysis results, means for receiving and analyzing user emotional data, means for adjusting the career plans and study plans based on the emotional data, means for transmitting the generated plans to the user's terminal, means for the user to confirm the transmitted plans, means for transmitting user feedback to the server, and means for readjusting the plans based on the feedback received by the server. This makes it possible to provide optimal career plans and study plans taking into account the user's emotional state, and to readjust the plans as necessary based on the user's feedback and emotional data.

[1729] "User" refers to an individual who uses this system to obtain a career plan and a study plan.

[1730] "Skills" refer to specific knowledge or techniques that a user possesses.

[1731] "Education level" refers to the user's educational background, such as the highest level of education and the degree obtained.

[1732] "Career" refers to the history of the jobs and tasks that a user has experienced.

[1733] "Goals" refer to the career objectives or achievements that a user wants to achieve.

[1734] "Terminal" refers to the electronic device used by a user to enter information and view plans.

[1735] "Server" refers to a central system that receives, stores, and analyzes user information, generates plans, and sends them to terminals.

[1736] "Database" refers to a data storage device for efficiently storing and managing user information and plans.

[1737] "Data analysis" refers to the process of deriving the optimal plan based on collected user information.

[1738] A "career plan" refers to the specific steps or plans a user takes to achieve their desired career goals.

[1739] A "learning plan" refers to a specific plan for a user to learn the knowledge and skills they need to acquire in order to achieve their goals.

[1740] "Emotional data" refers to information that indicates a user's emotional state, such as stress, happiness, or anxiety.

[1741] "Feedback" refers to the evaluations and comments that users make on proposed plans.

[1742] "Recalibration" refers to the process of revising and re-optimizing a plan based on user feedback and sentiment data.

[1743] "Market trends" refers to information that indicates the situation based on current economic conditions and industry trends.

[1744] "Job information" refers to information about job content and employment conditions published by companies and organizations.

[1745] "Visually easy to understand" refers to a format that is displayed graphically so that users can easily grasp the content.

[1746] This invention relates to an AI system that proposes optimal career and study plans to help users achieve their career goals. The system generates appropriate plans based on the user's skills, educational level, career history, and goals, and also has the ability to recognize the user's emotions and adjust the plans accordingly.

[1747] System configuration

[1748] 1. User Interface

[1749] Users enter information about their skills, education level, background, goals, and emotions using forms on websites and mobile applications.

[1750] 2. Data Transmission

[1751] The terminal transmits the entered information to the server using a secure protocol (e.g., HTTPS).

[1752] 3. Data Storage

[1753] The server stores the received information in a database, which allows efficient management and rapid access to large amounts of data.

[1754] 4. Data Analysis

[1755] The server runs AI algorithms based on the stored information, analyzing the user's skills, education level, background, and goals to generate optimal career and learning plans.

[1756] 5. Emotion Engine

[1757] The server uses an emotion engine to analyze emotion data from user input and dialogue history, thereby recognizing the user's emotional state and reflecting it in the career plan.

[1758] 6. Plan generation and consideration of emotional feedback

[1759] The server combines the analysis results of the AI ​​algorithm with feedback from the emotion engine to generate optimal career and study plans for the user. For example, if the user is feeling stressed, the server can include suggestions for relaxing study methods.

[1760] 7. Plan Presentation

[1761] The server encodes the generated plan in JSON format or similar and sends it to the device, which then displays the received plan in a visually easy-to-understand format.

[1762] 8. Feedback and Recalibration

[1763] The user inputs feedback on the received plan and sends it to the server, which then readjusts the career and learning plans based on this feedback and emotional data.

[1764] Specific examples

[1765] For example, consider a user who has a goal of becoming an AI engineer. The user inputs "Python" and "Basic Mathematics" as their current skills, "University Graduate" as their education level, "Data Analyst" as their career, and "Feeling Stressed" as their emotional state.

[1766] Based on this information, the server analyzes that having skills in "machine learning" and "data science" is important for becoming an AI engineer. In addition, the emotion engine recognizes that the user is feeling stressed and suggests a learning plan that includes "taking an online course" and "relaxation sessions" as a way to relax.

[1767] Prompt Sentence Examples

[1768] "Please suggest a career plan for becoming an AI engineer. Your current skills are basic Python and math, you have graduated from university, and you are working as a data analyst. Please also consider the stress you are experiencing."

[1769] By inputting these prompts into a generative AI model, a career and learning plan optimized for the user's needs and emotional state is provided. Through this process, users are provided with concrete steps to effectively advance their careers, helping them achieve their goals while reducing emotional burden.

[1770] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1771] Step 1:

[1772] Users enter information about their skills, education level, career history, goals, and emotions.

[1773] Input: User skills, education level, background, goals, emotions (e.g., "Python," "College graduate," "Data analyst," "I want to be an AI engineer," "I'm stressed").

[1774] What happens: A user fills out a form on a website or mobile application.

[1775] Output: The input information is encoded in JSON format.

[1776] Step 2:

[1777] The terminal transmits the entered information to the server using a secure protocol (e.g., HTTPS).

[1778] Input: User information encoded in JSON format.

[1779] Operation: After the send button is pressed, the device sends the data to the server using HTTPS.

[1780] Output: The encoded JSON data is sent to the server.

[1781] Step 3:

[1782] The server stores the received information in a database.

[1783] Input: User information encoded in JSON format.

[1784] How it works: The server parses the information and stores it in the appropriate tables in the database. Each item (skills, education level, career history, goals, emotional data) is associated with the user ID.

[1785] Output: The user information is saved in the database.

[1786] Step 4:

[1787] The server runs AI algorithms based on the stored information and performs data analysis.

[1788] Input: User's skills, education level, background, and goals retrieved from the database.

[1789] How it works: AI algorithms analyze this information to identify the best skill sets and learning content for your goals.

[1790] Output: Specific career and learning plans, such as "take a machine learning course" or "study data science."

[1791] Step 5:

[1792] The server receives and analyzes the user's emotion data.

[1793] Input: User emotion data retrieved from the database.

[1794] How it works: The emotion engine analyzes emotion data and identifies emotional states such as "feeling stressed."

[1795] Output: The user's emotional state (e.g., stress, happiness, anxiety).

[1796] Step 6:

[1797] The server integrates the analysis results of the AI ​​algorithm with feedback from the emotion engine to generate optimal career and learning plans.

[1798] Input: Analysis results of AI algorithm, feedback from emotion engine.

[1799] How it works: The server integrates these data and generates a plan that takes into account the user's emotional state, for example, "a study plan that includes relaxation sessions to reduce stress."

[1800] Output: Optimized career and study plans.

[1801] Step 7:

[1802] The server encodes the generated plan in JSON format and sends it to the terminal.

[1803] Input: Generated career and study plans.

[1804] How it works: The server encodes the plan into JSON format and sends it to the device.

[1805] Output: The encoded JSON data.

[1806] Step 8:

[1807] The terminal decodes the received JSON data and displays it in a visually easy-to-understand format.

[1808] Input: JSON data received from the server.

[1809] How it works: The device decodes the data and displays it in a visually understandable format such as a timeline or list. For example, "Online courses taken" or "Relaxation sessions attended."

[1810] Output: Career and study plans in a user-readable format.

[1811] Step 9:

[1812] The user inputs feedback on the plan and sends it to the server.

[1813] Input: Your rating and comments on the plan (e.g., "There's too much to learn").

[1814] How it works: The user enters their feedback and presses the submit button to send it to the server.

[1815] Output: Feedback information is sent to the server.

[1816] Step 10:

[1817] The server readjusts career and learning plans based on the feedback received.

[1818] Input: User feedback and sentiment data.

[1819] How it works: Based on feedback and sentiment data, the AI ​​algorithm is re-run to optimize the plan, for example by reducing learnings and splitting the progress schedule.

[1820] Output: A realigned career and study plan.

[1821] This series of processing flows allows users to obtain optimal career and study plans while taking into consideration their own emotional state.

[1822] (Application example 2)

[1823] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1824] Previous career and study plan generation systems did not take into account the user's emotional state or psychological burden, and were not specialized for in-store counseling support. As a result, they were unable to make optimal suggestions based on the user's emotional state, making it difficult to propose career plans that would minimize stress for users. Furthermore, because they did not support in-store counseling support, it was difficult to provide consistent service to users in-store.

[1825] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing the customer's emotions and adjusting the plan based on these emotions, means for inputting the user's skills, educational level, work history, and goals and generating optimal career and study plans based on this information, and means for transmitting the generated plans to the user's terminal and readjusting the plans based on the user's opinions. This makes it possible to propose optimal career and study plans based on the user's emotional state, and also enables counseling support in physical stores and stress reduction for users.

[1826] "User" refers to a person who uses the system.

[1827] "Skills" refers to the abilities and knowledge related to a particular task or occupation.

[1828] "Education level" refers to the level of education or academic background of the user.

[1829] "Work history" refers to the occupations and work experiences that a user has had in the past.

[1830] "Goals" refers to the career or academic goals that the user is trying to achieve in the future.

[1831] "Input means" refers to the method or device by which a user provides information about himself or herself to the system.

[1832] "Server" refers to a computer system that processes, stores, analyzes, and transmits information received from users.

[1833] "Data Storage Device" means a database or other storage device for storing user-provided information.

[1834] "Information analysis" refers to the process by which the server utilizes data received from the user to generate specific results or recommendations.

[1835] A "career plan" refers to a plan that includes procedures or steps to achieve a desired career for a user.

[1836] A "learning plan" refers to a plan for a user to acquire the knowledge and skills necessary to achieve a goal.

[1837] "Emotion analysis" refers to recognizing a user's emotions and psychological state and analyzing that information.

[1838] "Opinions" refer to feedback and requests that users provide regarding the generated plan.

[1839] "Adjustment means" refers to methods or devices that modify or improve the plan based on the user's opinions or emotional state.

[1840] "Terminal" refers to the computer or smart device that a user uses to interact with the system.

[1841] This invention relates to an AI system that proposes optimal career and study plans for users to achieve their career goals. The system generates plans based on the user's skills, educational level, work history, and goals, and also has the ability to adjust the plans by recognizing the user's emotions.

[1842] System configuration

[1843] 1. User Interface

[1844] Users input their skills, educational level, work history, and goals using devices such as smartphones or tablets. The system is intended to be used as a career counseling support tool in brick-and-mortar stores.

[1845] 2. Data Transmission

[1846] The user terminal sends the entered information to the server using a secure protocol (e.g., HTTPS), which helps protect privacy.

[1847] 3. Data Storage

[1848] The server stores the received information in a database (e.g., MySQL, PostgreSQL). Each user's information is managed efficiently and data access is rapid.

[1849] 4. Data Analysis

[1850] The server runs AI algorithms based on the stored information to generate optimal career and learning plans based on the user's skills, educational level, work history, and goals. The analysis uses AI models (e.g., machine learning libraries TensorFlow and PyTorch).

[1851] 5. Emotion analysis

[1852] The server uses an emotion engine (e.g., NLTK, TextBlob) that recognizes emotions from user input and dialogue history, thereby determining the user's psychological state and reflecting the feedback in the plan generation.

[1853] 6. Plan generation and consideration of emotional feedback

[1854] The server generates optimal career and study plans for users based on the analysis results of the AI ​​algorithm and feedback from the emotion engine. For example, if a user is feeling stressed, it will suggest relaxation methods for studying (e.g., using a meditation app or engaging in fitness activities).

[1855] 7. Presenting the plan

[1856] The server sends the generated plan to the user's terminal, where the plan is displayed in a visually easy-to-understand format.

[1857] 8. Feedback and Recalibration

[1858] The server receives feedback and emotional data provided by users and adjusts their career and learning plans accordingly, enabling the system to continuously provide optimal suggestions tailored to each individual user.

[1859] Specific examples

[1860] Specific hardware examples

[1861] Smartphones and tablets (e.g. iPhone, iPad, Samsung Galaxy)

[1862] Specific software examples

[1863] Frameworks used for REST API development (e.g., Flask, Django)

[1864] Simple sentiment analysis library (e.g. NLTK, TextBlob)

[1865] Example prompts to input to the generative AI model

[1866] What are your career goals? Tell us about your current skills, education level, and background. Also, describe your current emotional state.

[1867] This system is specialized for supporting career counseling in brick-and-mortar stores, and is able to propose optimal career plans that take into account the user's emotions. In this way, it is possible to provide users with effective career counseling with less stress.

[1868] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1869] Step 1:

[1870] The user enters information about themselves into the device, such as their skills, educational level, work history, goals, and emotional state (e.g., "I'm feeling stressed"). This information is collected through the app's user interface. The input data is structured in a standard format, such as JSON.

[1871] Step 2:

[1872] The terminal sends the entered information to the server. The data sent is encrypted using a secure protocol (e.g. HTTPS). The server stores the received data in a database. The database has a table for each user, allowing for efficient data reference.

[1873] Step 3:

[1874] The server analyzes the information stored in the data storage. Specifically, it uses AI algorithms to generate career and study plans suited to the user's skills, educational level, work history, and goals. The AI ​​algorithms used utilize machine learning frameworks (e.g., TensorFlow, PyTorch).

[1875] Step 4:

[1876] The server analyzes the user's emotions using a sentiment analysis engine. It recognizes emotions based on the input text and dialogue history. The sentiment analysis engine used uses a natural language processing library (e.g., NLTK, TextBlob).

[1877] Step 5:

[1878] The server generates optimal career and study plans based on the results of the AI ​​model analysis and feedback from emotion analysis. For example, if a user is feeling stressed, it will provide a study plan incorporating relaxation techniques. The generated plans are encoded in JSON format or similar.

[1879] Step 6:

[1880] The server sends the generated career plan and study plan to the terminal, which displays the received data in a visually easy-to-understand format (e.g., charts and lists).

[1881] Step 7:

[1882] The user checks the provided career plan and learning plan and inputs feedback. The user also inputs their evaluation of the plan and any additional requests. The feedback data is then sent back to the server.

[1883] Step 8:

[1884] The server analyzes the user's feedback and adjusts the career and learning plans as needed. This can be done using machine learning algorithms or rule-based engines. The adjusted plans are then sent back to the user's device, completing the feedback loop for the entire system.

[1885] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1886] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1887] 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 the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1888] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1889] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1890] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1891] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1892] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1893] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1894] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1895] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1896] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1897] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1898] 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.

[1899] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1900] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1901] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[1902] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1903] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1904] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1905] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1906] The following is further disclosed regarding the above embodiment.

[1907] (Claim 1)

[1908] a means for users to input their skills, education level, background, and goals;

[1909] means for transmitting the input information to a server;

[1910] means for the server to store the received information in a database;

[1911] a means for performing data analysis based on the stored information;

[1912] A means for generating optimal career and study plans based on the analysis results;

[1913] means for transmitting the generated plan to a user terminal;

[1914] A means for the user to confirm the submitted plan;

[1915] means for transmitting user feedback to a server;

[1916] a means for the server to readjust the plan based on the feedback it receives; and

[1917] A system including:

[1918] (Claim 2)

[1919] 10. The system of claim 1, further comprising means for collecting market trend and job information and generating a career plan and a study plan for the user based thereon.

[1920] (Claim 3)

[1921] 2. The system according to claim 1, further comprising means for displaying the plan in a visually easy-to-understand format on the user's terminal.

[1922] "Example 1"

[1923] (Claim 1)

[1924] a means for the user to input their abilities, educational level, work history, and goals;

[1925] means for transmitting the input data to a computer;

[1926] means for storing the data received by the computer in a data storage device;

[1927] means for performing information processing based on the stored data;

[1928] A means for generating an optimal career plan and study plan based on the information processing results;

[1929] means for transmitting the generated plan to a user's information processing device;

[1930] a means for the user to verify the submitted plan;

[1931] means for transmitting user comments to a computer;

[1932] a means for the computer to readjust its plan based on the feedback it receives; and

[1933] A system including:

[1934] (Claim 2)

[1935] 2. The system according to claim 1, further comprising means for collecting information on economic trends and employment and generating a career plan and a study plan for the user based thereon.

[1936] (Claim 3)

[1937] 10. The system of claim 1, further comprising means for displaying the plan in a visually easy-to-understand format on the user's information processing device.

[1938] "Application Example 1"

[1939] (Claim 1)

[1940] a means for users to input their skills, education level, background, and goals;

[1941] means for transmitting the input information to a server;

[1942] means for the server to store the received information in a database;

[1943] a means for performing data analysis based on the stored information;

[1944] A means for generating optimal career and study plans based on the analysis results;

[1945] means for transmitting the generated plan to a user terminal;

[1946] A means for the user to confirm the submitted plan;

[1947] means for transmitting user feedback to a server;

[1948] a means for the server to readjust the plan based on the feedback it receives; and

[1949] A means for managing payments for courses of study and services under the proposed plan;

[1950] A means to provide status and tracking of funds used to achieve career plans;

[1951] A system including:

[1952] (Claim 2)

[1953] 10. The system of claim 1, further comprising means for collecting market trend and job information and generating a career plan and a study plan for the user based thereon.

[1954] (Claim 3)

[1955] 2. The system according to claim 1, further comprising means for displaying the plan in a visually easy-to-understand format on the user's terminal.

[1956] "Example 2: Combining Emotion Engines"

[1957] (Claim 1)

[1958] a means for users to input their skills, education level, background, and goals;

[1959] means for transmitting the input information to a server;

[1960] means for the server to store the received information in a database;

[1961] a means for performing data analysis based on the stored information;

[1962] A means for generating optimal career and study plans based on the analysis results;

[1963] means for receiving and analyzing user emotion data;

[1964] a means for adjusting career and learning plans based on emotion data;

[1965] means for transmitting the generated plan to a user terminal;

[1966] A means for the user to confirm the submitted plan;

[1967] means for transmitting user feedback to a server;

[1968] a means for the server to readjust the plan based on the feedback it receives; and

[1969] A system including:

[1970] (Claim 2)

[1971] 10. The system of claim 1, further comprising means for collecting market trend and job information and generating a career plan and a study plan for the user based thereon.

[1972] (Claim 3)

[1973] 2. The system according to claim 1, further comprising means for displaying the plan in a visually easy-to-understand format on the user's terminal.

[1974] "Application example 2 when combining emotion engines"

[1975] (Claim 1)

[1976] a means for the user to input skills, educational level, work history, and goals;

[1977] means for transmitting the input information to a server;

[1978] means for storing the information received by the server in a data storage device;

[1979] A means for performing information analysis based on the stored information;

[1980] A means for generating optimal career and study plans based on the analysis results;

[1981] means for transmitting the generated plan to a user terminal;

[1982] a means for the user to verify the submitted plan;

[1983] means for transmitting user opinions to a server;

[1984] a means for the server to readjust its plans based on the feedback it receives; and

[1985] A means of analyzing customer sentiment and adjusting plans based on this sentiment;

[1986] A system including:

[1987] (Claim 2)

[1988] 10. The system of claim 1, further comprising means for collecting market trend and job search information and generating a career and study plan for the user based thereon.

[1989] (Claim 3)

[1990] 2. The system according to claim 1, further comprising means for displaying the plan in a visually easy-to-understand format on the user's terminal. [Explanation of symbols]

[1991] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for users to input their skills, education level, background, and goals; means for transmitting the input information to a server; means for the server to store the received information in a database; a means for performing data analysis based on the stored information; A means for generating optimal career and study plans based on the analysis results; means for transmitting the generated plan to a user terminal; A means for the user to confirm the submitted plan; means for transmitting user feedback to a server; a means for the server to readjust the plan based on the feedback it receives; and A system including:

2. 2. The system according to claim 1, further comprising means for collecting market trend and job information and generating a career plan and a study plan for the user based thereon.

3. 2. The system according to claim 1, further comprising means for displaying the plan in a visually easy-to-understand format on the user's terminal.

Images