system

Abstract

We provide the system. [Solution] A means of acquiring personal information from an input device, converting it into a data format, and transmitting it, A means of analyzing the characteristics of received personal information using an analysis device to identify suitability, Based on the analyzed characteristics and aptitudes, a means for selecting a school or occupation, A means of constructing a career plan based on the selected educational institution or occupation and proposing it via an output device, A means of acquiring information through dialogue with an individual using a speech recognition device, A means for converting the voice input from the aforementioned individual into text data and storing it in a database, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a conventional carrier selection support system, it is difficult for a student to clarify a future vision because it is impossible to propose a sufficiently personalized school or career choice based on an individual's aptitude and interests. Also, there is a problem that it is difficult to select useful information from an overabundance of information and the student feels anxiety about the selection.

Means for Solving the Problems

[0005] This invention provides a means of identifying an individual's strengths and aptitudes by acquiring an individual's academic performance, activity history, and interest information from an input device and analyzing it in detail with an analysis device. Based on the analysis results, it selects the optimal educational institution or occupation and constructs and proposes a career plan accordingly, thereby enabling support optimized for each individual's aptitudes. Furthermore, by conducting long-term simulations for the selected career, it helps to clarify the individual's future vision.

[0006] "Personal information" refers to any data relating to an individual, including their academic performance, activity history, and interests.

[0007] An "input device" refers to a terminal or interface used by a user to input information.

[0008] A "data format" is a specific format into which information is converted for efficient exchange and processing.

[0009] An "analysis device" is a computer device that analyzes received data and performs processing to identify its characteristics and suitability.

[0010] "Characteristics" refer to the unique features, personality traits, and behavioral patterns of each individual user.

[0011] "Aptitude" refers to the ability or characteristics that indicate an individual's degree of suitability for a particular career path or occupation.

[0012] "Places to attend" refers to universities or specialized institutions that users are considering attending.

[0013] "Occupation" refers to the job and career options available to the user.

[0014] A "career plan" is a plan designed based on a user's characteristics and aptitudes, outlining their future career path and career aspirations.

[0015] The "output device" is a display or other display device for presenting analysis results and proposals to the user.

[0016] "Simulation" refers to a simulation experiment or calculation for predicting future results based on certain conditions and situations.

Brief Explanation of Drawings

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

Mode for Carrying Out the Invention

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

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

[0020] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

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

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

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

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

[0025] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0038] This invention is a system that proposes career paths and educational options suitable for individuals, and includes an input device, a data analysis device, a career proposal generation device, and an output device.

[0039] First, the user enters their academic record, activity history, and areas of interest into the input device. The terminal is designed to convert this information into the appropriate data format, encrypt it, and send it to the server.

[0040] The server analyzes the received data using an analysis device to identify the user's characteristics and aptitudes. This analysis uses machine learning algorithms and other methods to extract patterns from the user's data and reveal features related to the user's abilities and interests.

[0041] Next, the server selects the most suitable educational institutions and occupations for the user based on the analysis results and generates a career plan. The career plan includes potential educational institutions, occupational options, necessary skills, and action plans. This information is formatted and presented to the user through an output device.

[0042] For example, if a user's interest lies in law and their past activity history supports this, the system will suggest legal educational institutions and related career options. In this case, for professions such as lawyer or legal consultant, specific steps to acquire the necessary skills and experience will also be provided.

[0043] Finally, the server performs a long-term career simulation based on the user's choices and presents the scenario to the user. This simulation allows the user to understand how their chosen path will unfold and what challenges and opportunities they will face at each stage of their future career.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] Users input their academic performance, activity history, and areas of interest into a terminal using an input device. This includes specific school grades, past activities, and areas of current interest.

[0047] Step 2:

[0048] The terminal receives the input information and converts it into a data format. This data is formatted into an easy-to-handle format, and the information is verified and supplemented as needed. Next, the terminal encrypts this data and sends it to the server via secure communication.

[0049] Step 3:

[0050] The server receives and decodes the data sent from the terminal. The received data is stored in a database and preprocessed to make it available for use in subsequent analysis steps.

[0051] Step 4:

[0052] The server uses analytical equipment to analyze data and identify user characteristics and aptitudes. Machine learning algorithms are applied to evaluate suitable fields and potential career paths based on the input information.

[0053] Step 5:

[0054] Based on the analysis results, the server generates educational options, occupations, and career plans tailored to the user's interests and characteristics. These plans include detailed information on recommended educational institutions, suitable occupations, and necessary skill sets.

[0055] Step 6:

[0056] The server formats the generated carrier plan and sends it to the device in an easy-to-understand format. The device receives this information and displays it visually to the user.

[0057] Step 7:

[0058] Users review the carrier plans displayed on their devices and make selections based on their interests and preferences. They clarify their expectations and concerns regarding the selected plan.

[0059] Step 8:

[0060] The server runs a long-term career simulation based on the user's choices. This simulation presents the future development and specific steps toward realizing the chosen path.

[0061] Step 9:

[0062] The server sends the simulation results to the terminal and presents the user with future career scenarios. The user can then use this as a reference to develop a concrete action plan.

[0063] (Example 1)

[0064] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0065] Conventional career planning systems merely presented standard plans without adequately considering individual characteristics and aptitudes. Therefore, they failed to support users in choosing the most suitable educational institutions or careers, making it difficult to maximize individual potential. This invention aims to provide more appropriate and specific career plans by analyzing diverse individual data.

[0066] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0067] In this invention, the server includes means for acquiring personal data from an information input device, converting it into a standard data format, and transmitting it; means for analyzing the characteristics of the received personal data using a machine learning algorithm to identify aptitudes; and means for selecting educational institutions and professional occupations based on the analyzed characteristics and aptitudes. This makes it possible to propose specific and practical career plans tailored to each individual user.

[0068] "Personal data" refers to information about an individual, including academic performance, activity history, and areas of interest.

[0069] An "information input device" refers to a device or interface used to acquire personal data, such as a computer input form or a scanner.

[0070] "Converting to a data format" means representing acquired data in a standard form, such as converting it to formats like JSON or XML.

[0071] A "machine learning algorithm" refers to a computational method for finding patterns in large amounts of data and making predictions or decisions based on those patterns.

[0072] "Analyzing characteristics and identifying aptitudes" is the process of using an individual's data to analyze their characteristics and qualities, and to reveal their individual abilities and aptitudes.

[0073] "Selecting educational institutions and professional occupations" refers to determining the most suitable learning environment and occupational position for an individual based on their analyzed characteristics and aptitudes.

[0074] A "career plan" is a plan that outlines the career direction and specific steps an individual should take to achieve their future.

[0075] This invention is a system for proposing a career plan tailored to an individual, and a specific embodiment thereof is shown here.

[0076] Users first input their data using an information input device. This data consists of academic performance, activity history, and areas of interest. The information input device typically involves computer input forms or scanners.

[0077] The terminal converts the acquired data into a standard data format. Specifically, formats such as JSON and XML are used, and data integrity checks and encryption are performed. For encryption, data security is ensured by using methods such as AES encryption. After that, the terminal sends the encrypted data to the server.

[0078] The server executes machine learning algorithms to analyze the received data. This analysis utilizes programming languages ​​such as Python and R, employing algorithms like the randomized forest algorithm and SVM (Support Vector Machine). This allows for the identification of individual user characteristics and aptitudes.

[0079] Based on the analysis results, the server selects the most suitable educational institutions and professional occupations for the user. In this selection process, the server refers to information in the database and lists career options that match the user's characteristics. As a result, a career plan is proposed to the user, providing information on necessary skills and qualifications to acquire.

[0080] Furthermore, the server simulates future activity scenarios based on the career plan selected by the user. This simulation takes into account economic indicators and industry trends related to the user's chosen path to predict future possibilities and risks.

[0081] For example, if a user is interested in the legal field, the system will suggest legal educational institutions and professions (e.g., lawyers or legal consultants) to that user. Specific guidance will also be provided regarding the qualifications and skills necessary for the user to pursue a legal career.

[0082] A concrete example of a prompt used in a generative AI model would be, "Please write a program that proposes the optimal career plan for a student who is interested in the field of law and aspires to become a lawyer."

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

[0084] Step 1:

[0085] Users input their academic performance, activity history, and areas of interest into an information input device. The input data is retrieved in text and numerical format and sent to the terminal. The output here is a collection of the data provided by the user.

[0086] Step 2:

[0087] The terminal converts the data received from the user into a standard format (e.g., JSON). At this stage, it performs a data integrity check to ensure there are no missing or abnormal values. After verification, the converted data is secured using AES encryption. The output is encrypted data, which is then sent to the server.

[0088] Step 3:

[0089] The server decrypts the encrypted data received from the terminal and performs analysis using a data analysis device. Here, machine learning algorithms (e.g., randomized forests, SVM) are used to extract patterns for identifying user characteristics and aptitudes. The input is the decrypted data, and the output is the characteristic and aptitude profile obtained through the analysis.

[0090] Step 4:

[0091] The server selects the most suitable educational institutions and professional occupations for the user based on the obtained profile. This process searches an internal database to identify candidates that match the analyzed characteristics and aptitudes. The input is the characteristics and aptitude profile, and the output is a list of selected career options.

[0092] Step 5:

[0093] The server constructs a career plan based on the selected career options. This plan details the proposed educational institutions and the skills and qualifications required for the chosen occupation. Furthermore, this plan serves as the basis for simulating the user's future career. The input is a list of career options, and the output is a detailed career plan.

[0094] Step 6:

[0095] The server runs a simulation of future activities based on the career plan. The simulation considers economic indicators and industry trends to predict the risks and possibilities of the career path chosen by the user. The input is the career plan, and the output is a report of the simulation results.

[0096] Step 7:

[0097] The server formats the simulation results and presents them to the user via the terminal. Through the visualized report on the screen, the user can gain a deeper understanding of their career options. The input is the simulation results, and the output is a visual report to the user.

[0098] (Application Example 1)

[0099] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0100] A challenge in providing optimal recommendations for individual career choices and educational selections is the difficulty in basing them on each individual's characteristics, aptitudes, and interests. Such recommendations need to consider not only past achievements but also current interests and future trends. Furthermore, instead of simply providing information in a one-way manner, it is necessary to obtain more precise information through dialogue with the individual and provide individually optimized recommendations.

[0101] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0102] In this invention, the server includes means for acquiring personal information from an input device, converting it into a data format, and transmitting it; means for analyzing the characteristics of the received personal information with an analysis device and identifying aptitudes; means for selecting educational institutions and occupations based on the analyzed characteristics and aptitudes; means for acquiring information through dialogue with the individual using a speech recognition device; and means for converting the voice input from the individual into text data and storing it in a database. This enables data collection through precise dialogue and highly adapted career proposals.

[0103] An "input device" is hardware or an interface for acquiring personal information, which allows a user to input their own data into the system.

[0104] An "analysis device" is hardware or software used to process received personal information and analyze its characteristics and aptitudes.

[0105] "Aptitude" refers to the abilities and tendencies that are suited to a particular school or occupation, based on an individual's characteristics and interests.

[0106] A "career plan" is a plan based on analysis results that includes the most suitable educational institution and occupational choice for an individual, and details the necessary skills and steps.

[0107] A "speech recognition device" is a device that converts an individual's voice into digital data and understands its content, and is part of an interactive interface.

[0108] "Voice input" refers to voice information emitted by an individual, and serves as a data source for a system to understand and process it.

[0109] A "database" is a collection of information that stores analyzed voice input data and personal information, and is used for later reference and processing.

[0110] The system for realizing this application consists of multiple devices and software to suggest the most suitable career path for an individual. First, the user uses an input device to enter their own information, such as academic performance, activity history, and interests. This input device includes smartphones and personal computers.

[0111] The terminal converts this information into an appropriate data format and sends it to the server via secure communication. Upon receiving this transmitted data, the server uses an analysis device to analyze the data and identify the user's characteristics and aptitudes. This analysis utilizes pattern recognition technology using machine learning algorithms, specifically libraries such as TENSORFLOW® and scikit-learn.

[0112] Furthermore, the server also collects information from interactions with the user using a speech recognition device. This interaction utilizes speech recognition software such as Google® Cloud Speech-to-Text. The user's voice input is converted to text and stored in the system's database.

[0113] Based on the analysis results, the server selects suitable educational institutions and occupations for the user and generates a career plan. This includes multiple options tailored to the user's interests and analyzed characteristics. This information is formatted and presented to the user through an output device. The optimal career path proposal also includes long-term simulations tailored to the user's preferences, and the accuracy of the simulations is enhanced using cloud computing resources from Azure® and AWS®.

[0114] For example, if a user expresses interest in "law" and their past activities support this, the system will suggest law-related educational institutions and careers. For instance, it might suggest specific steps to pursue law school or become a legal professional.

[0115] An example of a prompt message would be: "Generate future career options based on the user's interests and past work experience. For example, if the user is interested in law, suggest related career paths."

[0116] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0117] Step 1:

[0118] Users input their academic records, activity history, and areas of interest using an input device. The entered data is converted into the appropriate data format via an application used on a smartphone or personal computer. This data is encrypted by the device and transmitted to the server in a secure manner.

[0119] Step 2:

[0120] The server passes the received data to the analysis device and begins data analysis. The input data includes numerical and text data, and machine learning algorithms are used to identify user characteristics and aptitudes during the analysis. Specific data processing includes normalization and one-hot encoding, resulting in the output of a vector representing user characteristics.

[0121] Step 3:

[0122] The server activates the speech recognition device and collects additional information through interaction with the user. The speech data is converted into text data in real time and stored in a database. This text data is used for analysis as supplementary data to understand the user's interests and emotions.

[0123] Step 4:

[0124] Based on the analysis results, the server selects educational and career options optimized for the user. This involves using a generative AI model, taking previously generated characteristic vectors and data supplemented by speech recognition as input, to generate career choices. These generated career options are then output as a set of recommendations based on the user's potential.

[0125] Step 5:

[0126] The server creates a detailed career plan based on the selected educational institution and occupation. This plan includes necessary skills and action steps, providing the user with concrete guidance. After formatting adjustments, the generated plan is presented to the user through an output device.

[0127] Step 6:

[0128] Depending on the user's selection, the server performs long-term simulations and provides a virtual scenario showing how that career choice will unfold. This simulation leverages cloud computing resources and outputs a detailed outlook on future challenges and opportunities.

[0129] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0130] This invention provides a system that utilizes emotional information in addition to personal information of users to propose more sophisticated career plans. The system includes an input device, an emotional engine, a data analysis device, a career proposal generation device, and an output device.

[0131] First, as the user inputs their academic performance, activity history, and areas of interest into the terminal via an input device, the emotion engine recognizes the user's emotions in real time. The terminal converts this information into a data format, encrypts it, and sends it to the server.

[0132] The server analyzes both the received personal data and emotional data using an analysis device to identify the user's characteristics and aptitudes. This analysis takes into account the emotional data provided by the emotion engine, reflecting, for example, the emotional responses a user has to a particular field of study or occupation, enabling a more individualized and accurate analysis.

[0133] Based on the analysis results, the server selects the most suitable educational institutions and occupations for the user. This selection also takes emotional compatibility into account, creating a career path that is likely to be emotionally satisfying for the user. In particular, by predicting long-term emotional changes and reflecting them in the career simulation, suggestions are made to enhance future satisfaction and happiness.

[0134] For example, if a user is interested in healthcare but the emotion engine detects that they are likely to experience psychological stress, the server will also suggest occupations that require similar skills but involve less psychological stress. In this way, the system presents educational options and occupations that are suitable for the user's emotional needs and offers them to the user via an output device.

[0135] Ultimately, the server sends simulation results and career plans to the terminal, allowing the user to plan their future based on the presented information. In this way, by combining emotional information, this system provides more beneficial and personalized suggestions to the user than existing career support systems.

[0136] The following describes the processing flow.

[0137] Step 1:

[0138] Users input their academic performance, activity history, and areas of interest into an input device. This includes grades in specific subjects, club activities participated in, and hobbies.

[0139] Step 2:

[0140] The device receives input from the user, and simultaneously, an emotion engine analyzes the user's facial expressions and voice to recognize the emotion at the time of input. This emotion data, along with the input information, is converted into a data format and sent to the server in an encrypted form.

[0141] Step 3:

[0142] The server processes personal information and emotional data received from the terminal using an analysis device. First, the data is decoded, and then analysis including emotional data is performed to identify the user's characteristics and aptitudes. At this stage, emotional data is taken into account to calculate, for example, an emotional prediction regarding areas of interest.

[0143] Step 4:

[0144] Based on the analysis results, the server takes feedback from the emotion engine into consideration when selecting schools or careers. It not only assesses aptitude and characteristics, but also forms options that are likely to emotionally satisfy the user.

[0145] Step 5:

[0146] The server generates a career plan that reflects emotional compatibility, incorporating specific actions such as required skills, experience, and recommended activities. This provides a career plan that is emotionally harmonious.

[0147] Step 6:

[0148] The server formats the generated carrier plan and sends it to the terminal. The terminal then presents the received information to the user in a visually easy-to-read format.

[0149] Step 7:

[0150] Users review the presented career plans, evaluate them, and make choices that match their desires and feelings.

[0151] Step 8:

[0152] The server runs a long-term career simulation based on the user's chosen career path, taking into account emotional changes. This simulation predicts the emotional impact of the chosen path and emotional adaptation, and uses the results to make suggestions that can increase user satisfaction.

[0153] Step 9:

[0154] The server sends the simulation results and final career plan to the terminal, which then presents them to the user. Based on this information, the user can then concretize and proceed with their actual action plan.

[0155] (Example 2)

[0156] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0157] Traditional career planning systems have suggested educational institutions and occupations based on individual attribute information, but they do not consider emotional information, making it difficult to provide suggestions that adequately consider the user's long-term satisfaction and suitability. Furthermore, they have been unable to provide plans that take into account the user's emotional fit to specific academic fields or occupations. Ultimately, there is a need for suggestions that aim to ensure users are emotionally satisfied with their chosen path and occupation.

[0158] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0159] In this invention, the server includes means for acquiring an individual's attributes from an input mechanism and converting them into a data structure, means for collecting emotional information at the time of input, and means for comprehensively analyzing the received individual's attributes and emotional information with an analysis device to identify characteristics and aptitudes. This makes it possible to suggest educational institutions and occupations that take into account the user's emotional compatibility and satisfaction.

[0160] "Personal attributes" refer to information about an individual, including their academic performance, activity history, and areas of interest.

[0161] An "input mechanism" refers to a device or means used by a user to input personal attributes into a terminal.

[0162] "Converting to a data structure" refers to converting acquired personal attribute and sentiment information into a format that can be processed by a computer (e.g., JSON or XML).

[0163] An "emotion recognition mechanism" refers to a technology or device that identifies and collects information about a user's emotions in real time during input.

[0164] An "analysis device" refers to a computer system used to analyze a user's characteristics and aptitudes using received personal attribute and emotional information.

[0165] "Integrated analysis" refers to a process that simultaneously considers an individual's attributes and emotional information, and then conducts a comprehensive evaluation of them.

[0166] "Identifying characteristics and aptitudes" refers to clarifying the user's characteristics and suitable fields based on analysis.

[0167] "Emotional compatibility" refers to an indicator that shows how emotionally suitable a particular school or occupation is for a user, based on the emotional information they provide.

[0168] "Long-term emotional change" refers to predicting how a user's emotional state will change over time.

[0169] "Career planning" refers to planning future strategies, including suitable educational institutions and occupations, based on analyzed data.

[0170] "Output mechanism" refers to a device or means for presenting analysis results or proposals to the user, and includes displays, printers, and the like.

[0171] This invention comprises a system equipped with a device (input mechanism) for users to input personal attribute information and an emotion recognition mechanism that recognizes emotional information from the user in real time. Users input information such as academic performance, activity history, and areas of interest into the terminal using a keyboard or touchscreen. The terminal converts this data into a format that can be processed by a computer and further collects emotional information via the emotion recognition mechanism. This system may utilize, for example, facial expression recognition software or voice analysis technology.

[0172] Next, the device encrypts this information and securely transmits it to the server. The server comprehensively analyzes the received data using an analysis device and utilizes a generative AI model to identify characteristics, aptitudes, and emotional compatibility. This analysis employs machine learning models and data mining techniques, and more precise analysis is performed by comparing the user's past data with emotional data.

[0173] Based on the analysis results, the server selects the most suitable educational institutions and occupations for the user. This selection also considers the user's emotional compatibility, and a career plan, including simulations, is created to ensure the user can pursue a long-term, satisfying career. The generated career plan is presented to the user via an output mechanism. Output devices such as displays and printers are possible, allowing the user to visually confirm the proposal.

[0174] For example, if a user is interested in engineering but feels anxious about giving presentations, we can suggest an engineering position that involves minimal interpersonal communication and is primarily desk-based. This also helps ensure the user's emotional stability.

[0175] An example of a prompt message would be: "Based on the user's interests and emotional data, please use AI to suggest the optimal career plan. If the user is not good at presentations, please also consider options that involve less interpersonal communication, even if they are technical positions."

[0176] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0177] Step 1:

[0178] Subject: User

[0179] Users input personal attribute information such as academic performance, activity history, and areas of interest into the terminal via an input mechanism. Users input this information using a keyboard or touchscreen. Additionally, the system captures the user's visual and auditory information, and an emotion recognition mechanism identifies the user's emotional state in real time. The input information is sent to the terminal as text data.

[0180] Step 2:

[0181] Subject: Important

[0182] The device integrates personal attribute information entered by the user with sentiment information acquired in real time and converts it into a digital data format (e.g., JSON or XML). This converted data is encrypted as a data stream and sent to the server using a secure protocol (e.g., HTTPS). The transmitted data includes the user's text information and sentiment information.

[0183] Step 3:

[0184] Subject: Server

[0185] The server passes the data received from the terminal to the analysis device. The analysis device uses a generative AI model to analyze the characteristics and suitability of the received data. This process employs machine learning algorithms to perform data analysis that integrates the user's personal attributes and emotional information. This analysis extracts the emotional responses and aptitudes that the user exhibits in specific fields, and generates analysis results.

[0186] Step 4:

[0187] Subject: Server

[0188] The server selects the most suitable educational institutions and occupations based on the analysis results. This selection takes into account the analyzed characteristics, aptitudes, and emotional compatibility. For example, if the analysis reveals that the user feels anxious about presentations, occupations with minimal interpersonal communication will be selected. This generated career plan is output as structured data.

[0189] Step 5:

[0190] Subject: Server

[0191] The generated career plan is presented to the user via an output mechanism. The server displays the information in a visually verifiable format using a display or printer. The user can then consider their own future plans based on this proposal. The generated career plan includes explanations based on the reasons for the proposal and emotional suitability.

[0192] (Application Example 2)

[0193] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0194] Existing career plan proposal systems have limitations in providing personalized suggestions that take into account user emotions. Furthermore, the personalization of the purchasing experience in electronic payment services is insufficient, and there is a need to improve customer satisfaction.

[0195] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0196] In this invention, the server includes means for acquiring personal information and emotional information from an input device, converting it into a data format, and transmitting it; means for analyzing the characteristics of the received personal information and emotional information with an analysis device and identifying aptitudes; means for selecting educational institutions and occupations that take emotional satisfaction into consideration based on the analyzed characteristics and aptitudes; and means for generating personalized purchase suggestions based on emotional information and presenting them via an output device. This makes it possible to propose personalized career plans and optimize the purchasing experience by utilizing the user's emotional information.

[0197] "Personal information" refers to attribute data about the user, such as performance, history, and interests.

[0198] "Emotional information" refers to data that detects and quantifies the user's emotional state in real time.

[0199] An "input device" refers to a device or interface that a user uses to input information.

[0200] "Means of converting and transmitting data" refers to the process of electronically processing input information, converting it to an appropriate format, and sending it to a server.

[0201] An "analysis device" refers to a system that performs analysis based on received information to investigate the user's characteristics and aptitudes.

[0202] "Characteristics" and "aptitudes" refer to attributes and categories based on a user's abilities, personality, and interests.

[0203] "Emotional satisfaction" refers to the emotional fulfillment a user experiences with a particular choice.

[0204] A "career plan" refers to designing a path regarding further education and employment.

[0205] "Purchase suggestions" refer to advice and recommendations for purchases generated based on the user's purchase history and emotional information.

[0206] "Output device" refers to a display or interface used to present generated information to the user.

[0207] This invention is a system that combines users' personal information and emotional information to provide specific and emotionally satisfying career plans and purchase suggestions.

[0208] In this system, users input personal information such as performance, history, and interests using input devices such as smartphones and tablets. Furthermore, a device with a built-in emotion engine analyzes the user's emotions in real time from their facial expressions and voice, and collects data. This emotion analysis uses a camera and microphone, and is implemented with facial recognition software and voice recognition algorithms.

[0209] The acquired information is converted into a data format and sent to a cloud server using encryption technology. Specifically, data transfer protocols and encryption algorithms are responsible for this process. The server utilizes cloud infrastructure such as AWS (Amazon Web Services) to provide secure data storage and powerful analytical capabilities.

[0210] On the server side, powerful data analysis tools integrate personal and emotional information to analyze user characteristics and aptitudes in detail. This analysis uses machine learning algorithms to automatically recognize data patterns, and further optimized career plans and purchase recommendations are generated by generative AI models.

[0211] Based on the analyzed information, the server provides users with educational institutions, career options, or purchasing experiences that are likely to be emotionally satisfying. The selected content is delivered to the user via an output device. For example, the information is displayed on the user's smart TV or mobile device using Samsung's SmartView app.

[0212] As a concrete application example, when a user displays a joyful expression while shopping, new products are recommended in real time based on that history. This creates a shopping experience that enhances user satisfaction.

[0213] An example of a prompt might be: "Show how to generate product suggestions that increase emotional satisfaction using the user's past purchase history and real-time sentiment data."

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

[0215] Step 1:

[0216] Users input their personal achievements, history, and interests using devices such as smartphones and tablets. In addition, an emotion engine analyzes the user's facial expressions and voice in real time through the device's camera and microphone to acquire emotional information. The input information is converted into a data format and prepared.

[0217] Step 2:

[0218] The device transmits the converted personal and emotional information to the cloud server according to an encryption protocol. Encryption technologies such as TLS (Transport Layer Security) are used in this process. The input is encrypted data, and the output is a secure data transfer to the server.

[0219] Step 3:

[0220] The server processes the received linked data using an analysis device to analyze user characteristics and aptitudes. First, a machine learning algorithm analyzes the dataset, evaluating multiple parameters to recognize patterns. This highlights characteristics related to the user's emotional responses.

[0221] Step 4:

[0222] Based on the analysis results, the server utilizes a generative AI model to design emotionally satisfying educational options, career choices, or purchasing experiences. Here, prompts are used specifically to guide the model and generate personalized recommendations. The input is the analyzed data, and the output is personalized recommendations.

[0223] Step 5:

[0224] The server delivers the generated career plans and purchase suggestions via the user's smart device or other output devices. This includes methods of providing information in a user-friendly format using notification systems and API interfaces. For example, execution in a SmartView app is being considered.

[0225] Step 6:

[0226] The user receives the presented information and makes a decision based on it. Based on these results, the server collects feedback and continuously trains the model to improve the accuracy of future suggestions. The input is the user's choice feedback, and the output is the enhanced AI model.

[0227] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0228] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0229] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0230] [Second Embodiment]

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

[0232] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0233] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0234] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0235] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0236] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0237] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0238] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0239] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0240] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0241] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0242] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0243] This invention is a system that proposes career paths and educational options suitable for individuals, and includes an input device, a data analysis device, a career proposal generation device, and an output device.

[0244] First, the user enters their academic record, activity history, and areas of interest into the input device. The terminal is designed to convert this information into the appropriate data format, encrypt it, and send it to the server.

[0245] The server analyzes the received data using an analysis device to identify the user's characteristics and aptitudes. This analysis uses machine learning algorithms and other methods to extract patterns from the user's data and reveal features related to the user's abilities and interests.

[0246] Next, the server selects the most suitable educational institutions and occupations for the user based on the analysis results and generates a career plan. The career plan includes potential educational institutions, occupational options, necessary skills, and action plans. This information is formatted and presented to the user through an output device.

[0247] For example, if a user's interest lies in law and their past activity history supports this, the system will suggest legal educational institutions and related career options. In this case, for professions such as lawyer or legal consultant, specific steps to acquire the necessary skills and experience will also be provided.

[0248] Finally, the server performs a long-term career simulation based on the user's choices and presents the scenario to the user. This simulation allows the user to understand how their chosen path will unfold and what challenges and opportunities they will face at each stage of their future career.

[0249] The following describes the processing flow.

[0250] Step 1:

[0251] Users input their academic performance, activity history, and areas of interest into a terminal using an input device. This includes specific school grades, past activities, and areas of current interest.

[0252] Step 2:

[0253] The terminal receives the input information and converts it into a data format. This data is formatted into an easy-to-handle format, and the information is verified and supplemented as needed. Next, the terminal encrypts this data and sends it to the server via secure communication.

[0254] Step 3:

[0255] The server receives and decodes the data sent from the terminal. The received data is stored in a database and preprocessed to make it available for use in subsequent analysis steps.

[0256] Step 4:

[0257] The server uses analytical equipment to analyze data and identify user characteristics and aptitudes. Machine learning algorithms are applied to evaluate suitable fields and potential career paths based on the input information.

[0258] Step 5:

[0259] Based on the analysis results, the server generates educational options, occupations, and career plans tailored to the user's interests and characteristics. These plans include detailed information on recommended educational institutions, suitable occupations, and necessary skill sets.

[0260] Step 6:

[0261] The server formats the generated carrier plan and sends it to the device in an easy-to-understand format. The device receives this information and displays it visually to the user.

[0262] Step 7:

[0263] Users review the carrier plans displayed on their devices and make selections based on their interests and preferences. They clarify their expectations and concerns regarding the selected plan.

[0264] Step 8:

[0265] The server runs a long-term career simulation based on the user's choices. This simulation presents the future development and specific steps toward realizing the chosen path.

[0266] Step 9:

[0267] The server sends the simulation results to the terminal and presents the user with future career scenarios. The user can then use this as a reference to develop a concrete action plan.

[0268] (Example 1)

[0269] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0270] Conventional career planning systems merely presented standard plans without adequately considering individual characteristics and aptitudes. Therefore, they failed to support users in choosing the most suitable educational institutions or careers, making it difficult to maximize individual potential. This invention aims to provide more appropriate and specific career plans by analyzing diverse individual data.

[0271] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0272] In this invention, the server includes means for acquiring personal data from an information input device, converting it into a standard data format, and transmitting it; means for analyzing the characteristics of the received personal data using a machine learning algorithm to identify aptitudes; and means for selecting educational institutions and professional occupations based on the analyzed characteristics and aptitudes. This makes it possible to propose specific and practical career plans tailored to each individual user.

[0273] "Personal data" refers to information about an individual, including academic performance, activity history, and areas of interest.

[0274] An "information input device" refers to a device or interface used to acquire personal data, such as a computer input form or a scanner.

[0275] "Converting to a data format" means representing acquired data in a standard form, such as converting it to formats like JSON or XML.

[0276] A "machine learning algorithm" refers to a computational method for finding patterns in large amounts of data and making predictions or decisions based on those patterns.

[0277] "Analyzing characteristics and identifying aptitudes" is the process of using an individual's data to analyze their characteristics and qualities, and to reveal their individual abilities and aptitudes.

[0278] "Selecting educational institutions and professional occupations" refers to determining the most suitable learning environment and occupational position for an individual based on their analyzed characteristics and aptitudes.

[0279] A "career plan" is a plan that outlines the career direction and specific steps an individual should take to achieve their future.

[0280] This invention is a system for proposing a career plan tailored to an individual, and a specific embodiment thereof is shown here.

[0281] Users first input their data using an information input device. This data consists of academic performance, activity history, and areas of interest. The information input device typically involves computer input forms or scanners.

[0282] The terminal converts the acquired data into a standard data format. Specifically, formats such as JSON or XML are used, and data integrity checks and encryption processing are performed. For encryption, for example, the AES encryption method is used to ensure data security. After that, the terminal sends the encrypted data to the server.

[0283] The server executes a machine learning algorithm to analyze the received data. For the analysis, programming languages such as Python or R are used, and algorithms such as the random forest algorithm and SVM (Support Vector Machine) are utilized. This enables the identification of the characteristics and suitability of individual users.

[0284] Based on the analysis results, the server selects the optimal educational institutions and professional occupations for the user. In this selection process, the server refers to the information in the database and lists career options that match the user's characteristics. As a result, a career plan is proposed to the user, providing information on the necessary skills and qualifications to be obtained.

[0285] Furthermore, the server simulates future activity scenarios based on the career plan selected by the user. This simulation takes into account economic indicators and industry trends related to the career path chosen by the user, predicting future possibilities and risks.

[0286] As a specific example, if the user is interested in the legal field, the system proposes legal-related educational institutions and occupations (e.g., lawyers or legal counselors) to that user. Specific guidance is also provided on the qualifications and skills required for the user to enter the legal profession.

[0287] Specific examples of the prompt text used in the generative AI model include "Write a program that proposes the optimal career plan for a student interested in the legal field and aiming to become a lawyer."

[0288] The flow of the specific process in Example 1 will be described using FIG. 11.

[0289] Step 1:

[0290] Users input their academic performance, activity history, and areas of interest into an information input device. The input data is retrieved in text and numerical format and sent to the terminal. The output here is a collection of the data provided by the user.

[0291] Step 2:

[0292] The terminal converts the data received from the user into a standard format (e.g., JSON). At this stage, it performs a data integrity check to ensure there are no missing or abnormal values. After verification, the converted data is secured using AES encryption. The output is encrypted data, which is then sent to the server.

[0293] Step 3:

[0294] The server decrypts the encrypted data received from the terminal and performs analysis using a data analysis device. Here, machine learning algorithms (e.g., randomized forests, SVM) are used to extract patterns for identifying user characteristics and aptitudes. The input is the decrypted data, and the output is the characteristic and aptitude profile obtained through the analysis.

[0295] Step 4:

[0296] The server selects the most suitable educational institutions and professional occupations for the user based on the obtained profile. This process searches an internal database to identify candidates that match the analyzed characteristics and aptitudes. The input is the characteristics and aptitude profile, and the output is a list of selected career options.

[0297] Step 5:

[0298] The server constructs a career plan based on the selected career options. This plan details the proposed educational institutions and the skills and qualifications required for the chosen occupation. Furthermore, this plan serves as the basis for simulating the user's future career. The input is a list of career options, and the output is a detailed career plan.

[0299] Step 6:

[0300] The server runs a simulation of future activities based on the career plan. The simulation considers economic indicators and industry trends to predict the risks and possibilities of the career path chosen by the user. The input is the career plan, and the output is a report of the simulation results.

[0301] Step 7:

[0302] The server formats the simulation results and presents them to the user via the terminal. Through the visualized report on the screen, the user can gain a deeper understanding of their career options. The input is the simulation results, and the output is a visual report to the user.

[0303] (Application Example 1)

[0304] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0305] A challenge in providing optimal recommendations for individual career choices and educational selections is the difficulty in basing them on each individual's characteristics, aptitudes, and interests. Such recommendations need to consider not only past achievements but also current interests and future trends. Furthermore, instead of simply providing information in a one-way manner, it is necessary to obtain more precise information through dialogue with the individual and provide individually optimized recommendations.

[0306] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0307] In this invention, the server includes means for acquiring personal information from an input device, converting it into a data format, and transmitting it; means for analyzing the characteristics of the received personal information using an analysis device and identifying the suitability; means for selecting a school to enter or a career based on the analyzed characteristics and suitability; means for acquiring information through interaction with an individual using a voice recognition device; and means for converting the voice input from the individual into text data and storing it in a database. Thereby, it becomes possible to collect data through refined interaction and provide highly adaptable career proposals.

[0308] The "input device" is hardware or an interface for acquiring personal information, enabling the user to input their own data into the system.

[0309] The "analysis device" is hardware or software for processing the received personal information and analyzing characteristics and suitability.

[0310] The "suitability" refers to the ability or tendency that matches a specific school to enter or a career based on an individual's characteristics and interests.

[0311] The "career plan" is a plan that includes the optimal school to enter or career choice for an individual based on the analysis results, and details the necessary skills and steps.

[0312] The "voice recognition device" is a device for converting an individual's voice into digital data and understanding the content, and is a part of the interactive interface.

[0313] The "voice input" refers to the voice information emitted by an individual and is a data source for the system to understand and process it.

[0314] The "database" is an aggregate of information that accumulates the analyzed voice input data and personal information and is used for later reference and processing.

[0315] The system for realizing this application consists of multiple devices and software to suggest the most suitable career path for an individual. First, the user uses an input device to enter their own information, such as academic performance, activity history, and interests. This input device includes smartphones and personal computers.

[0316] The terminal converts this information into an appropriate data format and sends it to the server via secure communication. Upon receiving this transmitted data, the server uses an analysis device to analyze the data and identify the user's characteristics and aptitudes. This analysis utilizes pattern recognition technology using machine learning algorithms, specifically leveraging libraries such as TensorFlow and scikit-learn.

[0317] Furthermore, the server also collects information from interactions with the user using a speech recognition device. This interaction utilizes speech recognition software such as Google Cloud Speech-to-Text. The user's voice input is converted to text and stored in the system's database.

[0318] Based on the analysis results, the server selects suitable educational institutions and occupations for the user and generates a career plan. This includes multiple options tailored to the user's interests and analyzed characteristics. This information is formatted and presented to the user through an output device. The optimal career path proposal also includes long-term simulations tailored to the user's preferences, and the accuracy of the simulations is enhanced using cloud computing resources from Azure and AWS.

[0319] For example, if a user expresses interest in "law" and their past activities support this, the system will suggest law-related educational institutions and careers. For instance, it might suggest specific steps to pursue law school or become a legal professional.

[0320] An example of a prompt message would be: "Generate future career options based on the user's interests and past work experience. For example, if the user is interested in law, suggest related career paths."

[0321] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0322] Step 1:

[0323] Users input their academic records, activity history, and areas of interest using an input device. The entered data is converted into the appropriate data format via an application used on a smartphone or personal computer. This data is encrypted by the device and transmitted to the server in a secure manner.

[0324] Step 2:

[0325] The server passes the received data to the analysis device and begins data analysis. The input data includes numerical and text data, and machine learning algorithms are used to identify user characteristics and aptitudes during the analysis. Specific data processing includes normalization and one-hot encoding, resulting in the output of a vector representing user characteristics.

[0326] Step 3:

[0327] The server activates the speech recognition device and collects additional information through interaction with the user. The speech data is converted into text data in real time and stored in a database. This text data is used for analysis as supplementary data to understand the user's interests and emotions.

[0328] Step 4:

[0329] Based on the analysis results, the server selects educational and career options optimized for the user. This involves using a generative AI model, taking previously generated characteristic vectors and data supplemented by speech recognition as input, to generate career choices. These generated career options are then output as a set of recommendations based on the user's potential.

[0330] Step 5:

[0331] The server creates a detailed career plan based on the selected educational institution and occupation. This plan includes necessary skills and action steps, providing the user with concrete guidance. After formatting adjustments, the generated plan is presented to the user through an output device.

[0332] Step 6:

[0333] Depending on the user's selection, the server performs long-term simulations and provides a virtual scenario showing how that career choice will unfold. This simulation leverages cloud computing resources and outputs a detailed outlook on future challenges and opportunities.

[0334] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0335] This invention provides a system that utilizes emotional information in addition to personal information of users to propose more sophisticated career plans. The system includes an input device, an emotional engine, a data analysis device, a career proposal generation device, and an output device.

[0336] First, as the user inputs their academic performance, activity history, and areas of interest into the terminal via an input device, the emotion engine recognizes the user's emotions in real time. The terminal converts this information into a data format, encrypts it, and sends it to the server.

[0337] The server analyzes both the received personal data and emotional data using an analysis device to identify the user's characteristics and aptitudes. This analysis takes into account the emotional data provided by the emotion engine, reflecting, for example, the emotional responses a user has to a particular field of study or occupation, enabling a more individualized and accurate analysis.

[0338] Based on the analysis results, the server selects the most suitable educational institutions and occupations for the user. This selection also takes emotional compatibility into account, creating a career path that is likely to be emotionally satisfying for the user. In particular, by predicting long-term emotional changes and reflecting them in the career simulation, suggestions are made to enhance future satisfaction and happiness.

[0339] For example, if a user is interested in healthcare but the emotion engine detects that they are likely to experience psychological stress, the server will also suggest occupations that require similar skills but involve less psychological stress. In this way, the system presents educational options and occupations that are suitable for the user's emotional needs and offers them to the user via an output device.

[0340] Ultimately, the server sends simulation results and career plans to the terminal, allowing the user to plan their future based on the presented information. In this way, by combining emotional information, this system provides more beneficial and personalized suggestions to the user than existing career support systems.

[0341] The following describes the processing flow.

[0342] Step 1:

[0343] Users input their academic performance, activity history, and areas of interest into an input device. This includes grades in specific subjects, club activities participated in, and hobbies.

[0344] Step 2:

[0345] The device receives input from the user, and simultaneously, an emotion engine analyzes the user's facial expressions and voice to recognize the emotion at the time of input. This emotion data, along with the input information, is converted into a data format and sent to the server in an encrypted form.

[0346] Step 3:

[0347] The server processes personal information and emotional data received from the terminal using an analysis device. First, the data is decoded, and then analysis including emotional data is performed to identify the user's characteristics and aptitudes. At this stage, emotional data is taken into account to calculate, for example, an emotional prediction regarding areas of interest.

[0348] Step 4:

[0349] Based on the analysis results, the server takes feedback from the emotion engine into consideration when selecting schools or careers. It not only assesses aptitude and characteristics, but also forms options that are likely to emotionally satisfy the user.

[0350] Step 5:

[0351] The server generates a career plan that reflects emotional compatibility, incorporating specific actions such as required skills, experience, and recommended activities. This provides a career plan that is emotionally harmonious.

[0352] Step 6:

[0353] The server formats the generated carrier plan and sends it to the terminal. The terminal then presents the received information to the user in a visually easy-to-read format.

[0354] Step 7:

[0355] Users review the presented career plans, evaluate them, and make choices that match their desires and feelings.

[0356] Step 8:

[0357] The server runs a long-term career simulation based on the user's chosen career path, taking into account emotional changes. This simulation predicts the emotional impact of the chosen path and emotional adaptation, and uses the results to make suggestions that can increase user satisfaction.

[0358] Step 9:

[0359] The server sends the simulation results and final career plan to the terminal, which then presents them to the user. Based on this information, the user can then concretize and proceed with their actual action plan.

[0360] (Example 2)

[0361] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0362] Traditional career planning systems have suggested educational institutions and occupations based on individual attribute information, but they do not consider emotional information, making it difficult to provide suggestions that adequately consider the user's long-term satisfaction and suitability. Furthermore, they have been unable to provide plans that take into account the user's emotional fit to specific academic fields or occupations. Ultimately, there is a need for suggestions that aim to ensure users are emotionally satisfied with their chosen path and occupation.

[0363] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0364] In this invention, the server includes means for acquiring an individual's attributes from an input mechanism and converting them into a data structure, means for collecting emotional information at the time of input, and means for comprehensively analyzing the received individual's attributes and emotional information with an analysis device to identify characteristics and aptitudes. This makes it possible to suggest educational institutions and occupations that take into account the user's emotional compatibility and satisfaction.

[0365] "Personal attributes" refer to information about an individual, including their academic performance, activity history, and areas of interest.

[0366] An "input mechanism" refers to a device or means used by a user to input personal attributes into a terminal.

[0367] "Converting to a data structure" refers to converting acquired personal attribute and sentiment information into a format that can be processed by a computer (e.g., JSON or XML).

[0368] An "emotion recognition mechanism" refers to a technology or device that identifies and collects information about a user's emotions in real time during input.

[0369] An "analysis device" refers to a computer system used to analyze a user's characteristics and aptitudes using received personal attribute and emotional information.

[0370] "Integrated analysis" refers to a process that simultaneously considers an individual's attributes and emotional information, and then conducts a comprehensive evaluation of them.

[0371] "Identifying characteristics and aptitudes" refers to clarifying the user's characteristics and suitable fields based on analysis.

[0372] "Emotional compatibility" refers to an indicator that shows how emotionally suitable a particular school or occupation is for a user, based on the emotional information they provide.

[0373] "Long-term emotional change" refers to predicting how a user's emotional state will change over time.

[0374] "Career planning" refers to planning future strategies, including suitable educational institutions and occupations, based on analyzed data.

[0375] "Output mechanism" refers to a device or means for presenting analysis results or proposals to the user, and includes displays, printers, and the like.

[0376] This invention comprises a system equipped with a device (input mechanism) for users to input personal attribute information and an emotion recognition mechanism that recognizes emotional information from the user in real time. Users input information such as academic performance, activity history, and areas of interest into the terminal using a keyboard or touchscreen. The terminal converts this data into a format that can be processed by a computer and further collects emotional information via the emotion recognition mechanism. This system may utilize, for example, facial expression recognition software or voice analysis technology.

[0377] Next, the device encrypts this information and securely transmits it to the server. The server comprehensively analyzes the received data using an analysis device and utilizes a generative AI model to identify characteristics, aptitudes, and emotional compatibility. This analysis employs machine learning models and data mining techniques, and more precise analysis is performed by comparing the user's past data with emotional data.

[0378] Based on the analysis results, the server selects the most suitable educational institutions and occupations for the user. This selection also considers the user's emotional compatibility, and a career plan, including simulations, is created to ensure the user can pursue a long-term, satisfying career. The generated career plan is presented to the user via an output mechanism. Output devices such as displays and printers are possible, allowing the user to visually confirm the proposal.

[0379] For example, if a user is interested in engineering but feels anxious about giving presentations, we can suggest an engineering position that involves minimal interpersonal communication and is primarily desk-based. This also helps ensure the user's emotional stability.

[0380] An example of a prompt message would be: "Based on the user's interests and emotional data, please use AI to suggest the optimal career plan. If the user is not good at presentations, please also consider options that involve less interpersonal communication, even if they are technical positions."

[0381] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0382] Step 1:

[0383] Subject: User

[0384] Users input personal attribute information such as academic performance, activity history, and areas of interest into the terminal via an input mechanism. Users input this information using a keyboard or touchscreen. Additionally, the system captures the user's visual and auditory information, and an emotion recognition mechanism identifies the user's emotional state in real time. The input information is sent to the terminal as text data.

[0385] Step 2:

[0386] Subject: Important

[0387] The device integrates personal attribute information entered by the user with sentiment information acquired in real time and converts it into a digital data format (e.g., JSON or XML). This converted data is encrypted as a data stream and sent to the server using a secure protocol (e.g., HTTPS). The transmitted data includes the user's text information and sentiment information.

[0388] Step 3:

[0389] Subject: Server

[0390] The server passes the data received from the terminal to the analysis device. The analysis device uses a generative AI model to analyze the characteristics and suitability of the received data. This process employs machine learning algorithms to perform data analysis that integrates the user's personal attributes and emotional information. This analysis extracts the emotional responses and aptitudes that the user exhibits in specific fields, and generates analysis results.

[0391] Step 4:

[0392] Subject: Server

[0393] The server selects the most suitable educational institutions and occupations based on the analysis results. This selection takes into account the analyzed characteristics, aptitudes, and emotional compatibility. For example, if the analysis reveals that the user feels anxious about presentations, occupations with minimal interpersonal communication will be selected. This generated career plan is output as structured data.

[0394] Step 5:

[0395] Subject: Server

[0396] The generated career plan is presented to the user via an output mechanism. The server displays the information in a visually verifiable format using a display or printer. The user can then consider their own future plans based on this proposal. The generated career plan includes explanations based on the reasons for the proposal and emotional suitability.

[0397] (Application Example 2)

[0398] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0399] Existing career plan proposal systems have limitations in providing personalized suggestions that take into account user emotions. Furthermore, the personalization of the purchasing experience in electronic payment services is insufficient, and there is a need to improve customer satisfaction.

[0400] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0401] In this invention, the server includes means for acquiring personal information and emotional information from an input device, converting it into a data format, and transmitting it; means for analyzing the characteristics of the received personal information and emotional information with an analysis device and identifying aptitudes; means for selecting educational institutions and occupations that take emotional satisfaction into consideration based on the analyzed characteristics and aptitudes; and means for generating personalized purchase suggestions based on emotional information and presenting them via an output device. This makes it possible to propose personalized career plans and optimize the purchasing experience by utilizing the user's emotional information.

[0402] "Personal information" refers to attribute data about the user, such as performance, history, and interests.

[0403] "Emotional information" refers to data that detects and quantifies the user's emotional state in real time.

[0404] An "input device" refers to a device or interface that a user uses to input information.

[0405] "Means of converting and transmitting data" refers to the process of electronically processing input information, converting it to an appropriate format, and sending it to a server.

[0406] An "analysis device" refers to a system that performs analysis based on received information to investigate the user's characteristics and aptitudes.

[0407] "Characteristics" and "aptitudes" refer to attributes and categories based on a user's abilities, personality, and interests.

[0408] "Emotional satisfaction" refers to the emotional fulfillment a user experiences with a particular choice.

[0409] A "career plan" refers to designing a path regarding further education and employment.

[0410] "Purchase suggestions" refer to advice and recommendations for purchases generated based on the user's purchase history and emotional information.

[0411] "Output device" refers to a display or interface used to present generated information to the user.

[0412] This invention is a system that combines users' personal information and emotional information to provide specific and emotionally satisfying career plans and purchase suggestions.

[0413] In this system, users input personal information such as performance, history, and interests using input devices such as smartphones and tablets. Furthermore, a device with a built-in emotion engine analyzes the user's emotions in real time from their facial expressions and voice, and collects data. This emotion analysis uses a camera and microphone, and is implemented with facial recognition software and voice recognition algorithms.

[0414] The acquired information is converted into a data format and sent to a cloud server using encryption technology. Specifically, data transfer protocols and encryption algorithms are responsible for this process. The server utilizes cloud infrastructure such as AWS (Amazon Web Services) to provide secure data storage and powerful analytical capabilities.

[0415] On the server side, powerful data analysis tools integrate personal and emotional information to analyze user characteristics and aptitudes in detail. This analysis uses machine learning algorithms to automatically recognize data patterns, and further optimized career plans and purchase recommendations are generated by generative AI models.

[0416] Based on the analyzed information, the server provides users with educational institutions, career options, or purchasing experiences that are likely to be emotionally satisfying. The selected content is delivered to the user via an output device. For example, the information is displayed on the user's smart TV or mobile device using Samsung's SmartView app.

[0417] As a concrete application example, when a user displays a joyful expression while shopping, new products are recommended in real time based on that history. This creates a shopping experience that enhances user satisfaction.

[0418] An example of a prompt might be: "Show how to generate product suggestions that increase emotional satisfaction using the user's past purchase history and real-time sentiment data."

[0419] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0420] Step 1:

[0421] Users input their personal achievements, history, and interests using devices such as smartphones and tablets. In addition, an emotion engine analyzes the user's facial expressions and voice in real time through the device's camera and microphone to acquire emotional information. The input information is converted into a data format and prepared.

[0422] Step 2:

[0423] The device transmits the converted personal and emotional information to the cloud server according to an encryption protocol. Encryption technologies such as TLS (Transport Layer Security) are used in this process. The input is encrypted data, and the output is a secure data transfer to the server.

[0424] Step 3:

[0425] The server processes the received linked data using an analysis device to analyze user characteristics and aptitudes. First, a machine learning algorithm analyzes the dataset, evaluating multiple parameters to recognize patterns. This highlights characteristics related to the user's emotional responses.

[0426] Step 4:

[0427] Based on the analysis results, the server utilizes a generative AI model to design emotionally satisfying educational options, career choices, or purchasing experiences. Here, prompts are used specifically to guide the model and generate personalized recommendations. The input is the analyzed data, and the output is personalized recommendations.

[0428] Step 5:

[0429] The server delivers the generated career plans and purchase suggestions via the user's smart device or other output devices. This includes methods of providing information in a user-friendly format using notification systems and API interfaces. For example, execution in a SmartView app is being considered.

[0430] Step 6:

[0431] The user receives the presented information and makes a decision based on it. Based on these results, the server collects feedback and continuously trains the model to improve the accuracy of future suggestions. The input is the user's choice feedback, and the output is the enhanced AI model.

[0432] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0433] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0434] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0435] [Third Embodiment]

[0436] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0437] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0438] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0439] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0440] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0441] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0442] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0443] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0444] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0445] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0446] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0447] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0448] This invention is a system that proposes career paths and educational options suitable for individuals, and includes an input device, a data analysis device, a career proposal generation device, and an output device.

[0449] First, the user enters their academic record, activity history, and areas of interest into the input device. The terminal is designed to convert this information into the appropriate data format, encrypt it, and send it to the server.

[0450] The server analyzes the received data using an analysis device to identify the user's characteristics and aptitudes. This analysis uses machine learning algorithms and other methods to extract patterns from the user's data and reveal features related to the user's abilities and interests.

[0451] Next, the server selects the most suitable educational institutions and occupations for the user based on the analysis results and generates a career plan. The career plan includes potential educational institutions, occupational options, necessary skills, and action plans. This information is formatted and presented to the user through an output device.

[0452] For example, if a user's interest lies in law and their past activity history supports this, the system will suggest legal educational institutions and related career options. In this case, for professions such as lawyer or legal consultant, specific steps to acquire the necessary skills and experience will also be provided.

[0453] Finally, the server performs a long-term career simulation based on the user's choices and presents the scenario to the user. This simulation allows the user to understand how their chosen path will unfold and what challenges and opportunities they will face at each stage of their future career.

[0454] The following describes the processing flow.

[0455] Step 1:

[0456] Users input their academic performance, activity history, and areas of interest into a terminal using an input device. This includes specific school grades, past activities, and areas of current interest.

[0457] Step 2:

[0458] The terminal receives the input information and converts it into a data format. This data is formatted into an easy-to-handle format, and the information is verified and supplemented as needed. Next, the terminal encrypts this data and sends it to the server via secure communication.

[0459] Step 3:

[0460] The server receives and decodes the data sent from the terminal. The received data is stored in a database and preprocessed to make it available for use in subsequent analysis steps.

[0461] Step 4:

[0462] The server uses analytical equipment to analyze data and identify user characteristics and aptitudes. Machine learning algorithms are applied to evaluate suitable fields and potential career paths based on the input information.

[0463] Step 5:

[0464] Based on the analysis results, the server generates educational options, occupations, and career plans tailored to the user's interests and characteristics. These plans include detailed information on recommended educational institutions, suitable occupations, and necessary skill sets.

[0465] Step 6:

[0466] The server formats the generated carrier plan and sends it to the device in an easy-to-understand format. The device receives this information and displays it visually to the user.

[0467] Step 7:

[0468] Users review the carrier plans displayed on their devices and make selections based on their interests and preferences. They clarify their expectations and concerns regarding the selected plan.

[0469] Step 8:

[0470] The server runs a long-term career simulation based on the user's choices. This simulation presents the future development and specific steps toward realizing the chosen path.

[0471] Step 9:

[0472] The server sends the simulation results to the terminal and presents the user with future career scenarios. The user can then use this as a reference to develop a concrete action plan.

[0473] (Example 1)

[0474] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0475] Conventional career planning systems merely presented standard plans without adequately considering individual characteristics and aptitudes. Therefore, they failed to support users in choosing the most suitable educational institutions or careers, making it difficult to maximize individual potential. This invention aims to provide more appropriate and specific career plans by analyzing diverse individual data.

[0476] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0477] In this invention, the server includes means for acquiring personal data from an information input device, converting it into a standard data format, and transmitting it; means for analyzing the characteristics of the received personal data using a machine learning algorithm to identify aptitudes; and means for selecting educational institutions and professional occupations based on the analyzed characteristics and aptitudes. This makes it possible to propose specific and practical career plans tailored to each individual user.

[0478] "Personal data" refers to information about an individual, including academic performance, activity history, and areas of interest.

[0479] An "information input device" refers to a device or interface used to acquire personal data, such as a computer input form or a scanner.

[0480] "Converting to a data format" means representing acquired data in a standard form, such as converting it to formats like JSON or XML.

[0481] A "machine learning algorithm" refers to a computational method for finding patterns in large amounts of data and making predictions or decisions based on those patterns.

[0482] "Analyzing characteristics and identifying aptitudes" is the process of using an individual's data to analyze their characteristics and qualities, and to reveal their individual abilities and aptitudes.

[0483] "Selecting educational institutions and professional occupations" refers to determining the most suitable learning environment and occupational position for an individual based on their analyzed characteristics and aptitudes.

[0484] A "career plan" is a plan that outlines the career direction and specific steps an individual should take to achieve their future.

[0485] This invention is a system for proposing a career plan tailored to an individual, and a specific embodiment thereof is shown here.

[0486] Users first input their data using an information input device. This data consists of academic performance, activity history, and areas of interest. The information input device typically involves computer input forms or scanners.

[0487] The terminal converts the acquired data into a standard data format. Specifically, formats such as JSON and XML are used, and data integrity checks and encryption are performed. For encryption, data security is ensured by using methods such as AES encryption. After that, the terminal sends the encrypted data to the server.

[0488] The server executes machine learning algorithms to analyze the received data. This analysis utilizes programming languages ​​such as Python and R, employing algorithms like the randomized forest algorithm and SVM (Support Vector Machine). This allows for the identification of individual user characteristics and aptitudes.

[0489] Based on the analysis results, the server selects the most suitable educational institutions and professional occupations for the user. In this selection process, the server refers to information in the database and lists career options that match the user's characteristics. As a result, a career plan is proposed to the user, providing information on necessary skills and qualifications to acquire.

[0490] Furthermore, the server simulates future activity scenarios based on the career plan selected by the user. This simulation takes into account economic indicators and industry trends related to the user's chosen path to predict future possibilities and risks.

[0491] For example, if a user is interested in the legal field, the system will suggest legal educational institutions and professions (e.g., lawyers or legal consultants) to that user. Specific guidance will also be provided regarding the qualifications and skills necessary for the user to pursue a legal career.

[0492] A concrete example of a prompt used in a generative AI model would be, "Please write a program that proposes the optimal career plan for a student who is interested in the field of law and aspires to become a lawyer."

[0493] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0494] Step 1:

[0495] Users input their academic performance, activity history, and areas of interest into an information input device. The input data is retrieved in text and numerical format and sent to the terminal. The output here is a collection of the data provided by the user.

[0496] Step 2:

[0497] The terminal converts the data received from the user into a standard format (e.g., JSON). At this stage, it performs a data integrity check to ensure there are no missing or abnormal values. After verification, the converted data is secured using AES encryption. The output is encrypted data, which is then sent to the server.

[0498] Step 3:

[0499] The server decrypts the encrypted data received from the terminal and performs analysis using a data analysis device. Here, machine learning algorithms (e.g., randomized forests, SVM) are used to extract patterns for identifying user characteristics and aptitudes. The input is the decrypted data, and the output is the characteristic and aptitude profile obtained through the analysis.

[0500] Step 4:

[0501] The server selects the most suitable educational institutions and professional occupations for the user based on the obtained profile. This process searches an internal database to identify candidates that match the analyzed characteristics and aptitudes. The input is the characteristics and aptitude profile, and the output is a list of selected career options.

[0502] Step 5:

[0503] The server constructs a career plan based on the selected career options. This plan details the proposed educational institutions and the skills and qualifications required for the chosen occupation. Furthermore, this plan serves as the basis for simulating the user's future career. The input is a list of career options, and the output is a detailed career plan.

[0504] Step 6:

[0505] The server runs a simulation of future activities based on the career plan. The simulation considers economic indicators and industry trends to predict the risks and possibilities of the career path chosen by the user. The input is the career plan, and the output is a report of the simulation results.

[0506] Step 7:

[0507] The server formats the simulation results and presents them to the user via the terminal. Through the visualized report on the screen, the user can gain a deeper understanding of their career options. The input is the simulation results, and the output is a visual report to the user.

[0508] (Application Example 1)

[0509] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0510] A challenge in providing optimal recommendations for individual career choices and educational selections is the difficulty in basing them on each individual's characteristics, aptitudes, and interests. Such recommendations need to consider not only past achievements but also current interests and future trends. Furthermore, instead of simply providing information in a one-way manner, it is necessary to obtain more precise information through dialogue with the individual and provide individually optimized recommendations.

[0511] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0512] In this invention, the server includes means for acquiring personal information from an input device, converting it into a data format, and transmitting it; means for analyzing the characteristics of the received personal information with an analysis device and identifying aptitudes; means for selecting educational institutions and occupations based on the analyzed characteristics and aptitudes; means for acquiring information through dialogue with the individual using a speech recognition device; and means for converting the voice input from the individual into text data and storing it in a database. This enables data collection through precise dialogue and highly adapted career proposals.

[0513] An "input device" is hardware or an interface for acquiring personal information, which allows a user to input their own data into the system.

[0514] An "analysis device" is hardware or software used to process received personal information and analyze its characteristics and aptitudes.

[0515] "Aptitude" refers to the abilities and tendencies that are suited to a particular school or occupation, based on an individual's characteristics and interests.

[0516] A "career plan" is a plan based on analysis results that includes the most suitable educational institution and occupational choice for an individual, and details the necessary skills and steps.

[0517] A "speech recognition device" is a device that converts an individual's voice into digital data and understands its content, and is part of an interactive interface.

[0518] "Voice input" refers to voice information emitted by an individual, and serves as a data source for a system to understand and process it.

[0519] A "database" is a collection of information that stores analyzed voice input data and personal information, and is used for later reference and processing.

[0520] The system for realizing this application consists of multiple devices and software to suggest the most suitable career path for an individual. First, the user uses an input device to enter their own information, such as academic performance, activity history, and interests. This input device includes smartphones and personal computers.

[0521] The terminal converts this information into an appropriate data format and sends it to the server via secure communication. Upon receiving this transmitted data, the server uses an analysis device to analyze the data and identify the user's characteristics and aptitudes. This analysis utilizes pattern recognition technology using machine learning algorithms, specifically leveraging libraries such as TensorFlow and scikit-learn.

[0522] Furthermore, the server also collects information from interactions with the user using a speech recognition device. This interaction utilizes speech recognition software such as Google Cloud Speech-to-Text. The user's voice input is converted to text and stored in the system's database.

[0523] Based on the analysis results, the server selects suitable educational institutions and occupations for the user and generates a career plan. This includes multiple options tailored to the user's interests and analyzed characteristics. This information is formatted and presented to the user through an output device. The optimal career path proposal also includes long-term simulations tailored to the user's preferences, and the accuracy of the simulations is enhanced using cloud computing resources from Azure and AWS.

[0524] For example, if a user expresses interest in "law" and their past activities support this, the system will suggest law-related educational institutions and careers. For instance, it might suggest specific steps to pursue law school or become a legal professional.

[0525] An example of a prompt message would be: "Generate future career options based on the user's interests and past work experience. For example, if the user is interested in law, suggest related career paths."

[0526] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0527] Step 1:

[0528] Users input their academic records, activity history, and areas of interest using an input device. The entered data is converted into the appropriate data format via an application used on a smartphone or personal computer. This data is encrypted by the device and transmitted to the server in a secure manner.

[0529] Step 2:

[0530] The server passes the received data to the analysis device and begins data analysis. The input data includes numerical and text data, and machine learning algorithms are used to identify user characteristics and aptitudes during the analysis. Specific data processing includes normalization and one-hot encoding, resulting in the output of a vector representing user characteristics.

[0531] Step 3:

[0532] The server activates the speech recognition device and collects additional information through interaction with the user. The speech data is converted into text data in real time and stored in a database. This text data is used for analysis as supplementary data to understand the user's interests and emotions.

[0533] Step 4:

[0534] Based on the analysis results, the server selects educational and career options optimized for the user. This involves using a generative AI model, taking previously generated characteristic vectors and data supplemented by speech recognition as input, to generate career choices. These generated career options are then output as a set of recommendations based on the user's potential.

[0535] Step 5:

[0536] The server creates a detailed career plan based on the selected educational institution and occupation. This plan includes necessary skills and action steps, providing the user with concrete guidance. After formatting adjustments, the generated plan is presented to the user through an output device.

[0537] Step 6:

[0538] Depending on the user's selection, the server performs long-term simulations and provides a virtual scenario showing how that career choice will unfold. This simulation leverages cloud computing resources and outputs a detailed outlook on future challenges and opportunities.

[0539] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0540] This invention provides a system that utilizes emotional information in addition to personal information of users to propose more sophisticated career plans. The system includes an input device, an emotional engine, a data analysis device, a career proposal generation device, and an output device.

[0541] First, as the user inputs their academic performance, activity history, and areas of interest into the terminal via an input device, the emotion engine recognizes the user's emotions in real time. The terminal converts this information into a data format, encrypts it, and sends it to the server.

[0542] The server analyzes both the received personal data and emotional data using an analysis device to identify the user's characteristics and aptitudes. This analysis takes into account the emotional data provided by the emotion engine, reflecting, for example, the emotional responses a user has to a particular field of study or occupation, enabling a more individualized and accurate analysis.

[0543] Based on the analysis results, the server selects the most suitable educational institutions and occupations for the user. This selection also takes emotional compatibility into account, creating a career path that is likely to be emotionally satisfying for the user. In particular, by predicting long-term emotional changes and reflecting them in the career simulation, suggestions are made to enhance future satisfaction and happiness.

[0544] For example, if a user is interested in healthcare but the emotion engine detects that they are likely to experience psychological stress, the server will also suggest occupations that require similar skills but involve less psychological stress. In this way, the system presents educational options and occupations that are suitable for the user's emotional needs and offers them to the user via an output device.

[0545] Ultimately, the server sends simulation results and career plans to the terminal, allowing the user to plan their future based on the presented information. In this way, by combining emotional information, this system provides more beneficial and personalized suggestions to the user than existing career support systems.

[0546] The following describes the processing flow.

[0547] Step 1:

[0548] Users input their academic performance, activity history, and areas of interest into an input device. This includes grades in specific subjects, club activities participated in, and hobbies.

[0549] Step 2:

[0550] The device receives input from the user, and simultaneously, an emotion engine analyzes the user's facial expressions and voice to recognize the emotion at the time of input. This emotion data, along with the input information, is converted into a data format and sent to the server in an encrypted form.

[0551] Step 3:

[0552] The server processes personal information and emotional data received from the terminal using an analysis device. First, the data is decoded, and then analysis including emotional data is performed to identify the user's characteristics and aptitudes. At this stage, emotional data is taken into account to calculate, for example, an emotional prediction regarding areas of interest.

[0553] Step 4:

[0554] Based on the analysis results, the server takes feedback from the emotion engine into consideration when selecting schools or careers. It not only assesses aptitude and characteristics, but also forms options that are likely to emotionally satisfy the user.

[0555] Step 5:

[0556] The server generates a career plan that reflects emotional compatibility, incorporating specific actions such as required skills, experience, and recommended activities. This provides a career plan that is emotionally harmonious.

[0557] Step 6:

[0558] The server formats the generated carrier plan and sends it to the terminal. The terminal then presents the received information to the user in a visually easy-to-read format.

[0559] Step 7:

[0560] Users review the presented career plans, evaluate them, and make choices that match their desires and feelings.

[0561] Step 8:

[0562] The server runs a long-term career simulation based on the user's chosen career path, taking into account emotional changes. This simulation predicts the emotional impact of the chosen path and emotional adaptation, and uses the results to make suggestions that can increase user satisfaction.

[0563] Step 9:

[0564] The server sends the simulation results and final career plan to the terminal, which then presents them to the user. Based on this information, the user can then concretize and proceed with their actual action plan.

[0565] (Example 2)

[0566] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0567] Traditional career planning systems have suggested educational institutions and occupations based on individual attribute information, but they do not consider emotional information, making it difficult to provide suggestions that adequately consider the user's long-term satisfaction and suitability. Furthermore, they have been unable to provide plans that take into account the user's emotional fit to specific academic fields or occupations. Ultimately, there is a need for suggestions that aim to ensure users are emotionally satisfied with their chosen path and occupation.

[0568] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0569] In this invention, the server includes means for acquiring an individual's attributes from an input mechanism and converting them into a data structure, means for collecting emotional information at the time of input, and means for comprehensively analyzing the received individual's attributes and emotional information with an analysis device to identify characteristics and aptitudes. This makes it possible to suggest educational institutions and occupations that take into account the user's emotional compatibility and satisfaction.

[0570] "Personal attributes" refer to information about an individual, including their academic performance, activity history, and areas of interest.

[0571] An "input mechanism" refers to a device or means used by a user to input personal attributes into a terminal.

[0572] "Converting to a data structure" refers to converting acquired personal attribute and sentiment information into a format that can be processed by a computer (e.g., JSON or XML).

[0573] An "emotion recognition mechanism" refers to a technology or device that identifies and collects information about a user's emotions in real time during input.

[0574] An "analysis device" refers to a computer system used to analyze a user's characteristics and aptitudes using received personal attribute and emotional information.

[0575] "Integrated analysis" refers to a process that simultaneously considers an individual's attributes and emotional information, and then conducts a comprehensive evaluation of them.

[0576] "Identifying characteristics and aptitudes" refers to clarifying the user's characteristics and suitable fields based on analysis.

[0577] "Emotional compatibility" refers to an indicator that shows how emotionally suitable a particular school or occupation is for a user, based on the emotional information they provide.

[0578] "Long-term emotional change" refers to predicting how a user's emotional state will change over time.

[0579] "Career planning" refers to planning future strategies, including suitable educational institutions and occupations, based on analyzed data.

[0580] "Output mechanism" refers to a device or means for presenting analysis results or proposals to the user, and includes displays, printers, and the like.

[0581] This invention comprises a system equipped with a device (input mechanism) for users to input personal attribute information and an emotion recognition mechanism that recognizes emotional information from the user in real time. Users input information such as academic performance, activity history, and areas of interest into the terminal using a keyboard or touchscreen. The terminal converts this data into a format that can be processed by a computer and further collects emotional information via the emotion recognition mechanism. This system may utilize, for example, facial expression recognition software or voice analysis technology.

[0582] Next, the device encrypts this information and securely transmits it to the server. The server comprehensively analyzes the received data using an analysis device and utilizes a generative AI model to identify characteristics, aptitudes, and emotional compatibility. This analysis employs machine learning models and data mining techniques, and more precise analysis is performed by comparing the user's past data with emotional data.

[0583] Based on the analysis results, the server selects the most suitable educational institutions and occupations for the user. This selection also considers the user's emotional compatibility, and a career plan, including simulations, is created to ensure the user can pursue a long-term, satisfying career. The generated career plan is presented to the user via an output mechanism. Output devices such as displays and printers are possible, allowing the user to visually confirm the proposal.

[0584] For example, if a user is interested in engineering but feels anxious about giving presentations, we can suggest an engineering position that involves minimal interpersonal communication and is primarily desk-based. This also helps ensure the user's emotional stability.

[0585] An example of a prompt message would be: "Based on the user's interests and emotional data, please use AI to suggest the optimal career plan. If the user is not good at presentations, please also consider options that involve less interpersonal communication, even if they are technical positions."

[0586] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0587] Step 1:

[0588] Subject: User

[0589] Users input personal attribute information such as academic performance, activity history, and areas of interest into the terminal via an input mechanism. Users input this information using a keyboard or touchscreen. Additionally, the system captures the user's visual and auditory information, and an emotion recognition mechanism identifies the user's emotional state in real time. The input information is sent to the terminal as text data.

[0590] Step 2:

[0591] Subject: Important

[0592] The device integrates personal attribute information entered by the user with sentiment information acquired in real time and converts it into a digital data format (e.g., JSON or XML). This converted data is encrypted as a data stream and sent to the server using a secure protocol (e.g., HTTPS). The transmitted data includes the user's text information and sentiment information.

[0593] Step 3:

[0594] Subject: Server

[0595] The server passes the data received from the terminal to the analysis device. The analysis device uses a generative AI model to analyze the characteristics and suitability of the received data. This process employs machine learning algorithms to perform data analysis that integrates the user's personal attributes and emotional information. This analysis extracts the emotional responses and aptitudes that the user exhibits in specific fields, and generates analysis results.

[0596] Step 4:

[0597] Subject: Server

[0598] The server selects the most suitable educational institutions and occupations based on the analysis results. This selection takes into account the analyzed characteristics, aptitudes, and emotional compatibility. For example, if the analysis reveals that the user feels anxious about presentations, occupations with minimal interpersonal communication will be selected. This generated career plan is output as structured data.

[0599] Step 5:

[0600] Subject: Server

[0601] The generated career plan is presented to the user via an output mechanism. The server displays the information in a visually verifiable format using a display or printer. The user can then consider their own future plans based on this proposal. The generated career plan includes explanations based on the reasons for the proposal and emotional suitability.

[0602] (Application Example 2)

[0603] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0604] Existing career plan proposal systems have limitations in providing personalized suggestions that take into account user emotions. Furthermore, the personalization of the purchasing experience in electronic payment services is insufficient, and there is a need to improve customer satisfaction.

[0605] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0606] In this invention, the server includes means for acquiring personal information and emotional information from an input device, converting it into a data format, and transmitting it; means for analyzing the characteristics of the received personal information and emotional information with an analysis device and identifying aptitudes; means for selecting educational institutions and occupations that take emotional satisfaction into consideration based on the analyzed characteristics and aptitudes; and means for generating personalized purchase suggestions based on emotional information and presenting them via an output device. This makes it possible to propose personalized career plans and optimize the purchasing experience by utilizing the user's emotional information.

[0607] "Personal information" refers to attribute data about the user, such as performance, history, and interests.

[0608] "Emotional information" refers to data that detects and quantifies the user's emotional state in real time.

[0609] An "input device" refers to a device or interface that a user uses to input information.

[0610] "Means of converting and transmitting data" refers to the process of electronically processing input information, converting it to an appropriate format, and sending it to a server.

[0611] An "analysis device" refers to a system that performs analysis based on received information to investigate the user's characteristics and aptitudes.

[0612] "Characteristics" and "aptitudes" refer to attributes and categories based on a user's abilities, personality, and interests.

[0613] "Emotional satisfaction" refers to the emotional fulfillment a user experiences with a particular choice.

[0614] A "career plan" refers to designing a path regarding further education and employment.

[0615] "Purchase suggestions" refer to advice and recommendations for purchases generated based on the user's purchase history and emotional information.

[0616] "Output device" refers to a display or interface used to present generated information to the user.

[0617] This invention is a system that combines users' personal information and emotional information to provide specific and emotionally satisfying career plans and purchase suggestions.

[0618] In this system, users input personal information such as performance, history, and interests using input devices such as smartphones and tablets. Furthermore, a device with a built-in emotion engine analyzes the user's emotions in real time from their facial expressions and voice, and collects data. This emotion analysis uses a camera and microphone, and is implemented with facial recognition software and voice recognition algorithms.

[0619] The acquired information is converted into a data format and sent to a cloud server using encryption technology. Specifically, data transfer protocols and encryption algorithms are responsible for this process. The server utilizes cloud infrastructure such as AWS (Amazon Web Services) to provide secure data storage and powerful analytical capabilities.

[0620] On the server side, powerful data analysis tools integrate personal and emotional information to analyze user characteristics and aptitudes in detail. This analysis uses machine learning algorithms to automatically recognize data patterns, and further optimized career plans and purchase recommendations are generated by generative AI models.

[0621] Based on the analyzed information, the server provides users with educational institutions, career options, or purchasing experiences that are likely to be emotionally satisfying. The selected content is delivered to the user via an output device. For example, the information is displayed on the user's smart TV or mobile device using Samsung's SmartView app.

[0622] As a concrete application example, when a user displays a joyful expression while shopping, new products are recommended in real time based on that history. This creates a shopping experience that enhances user satisfaction.

[0623] An example of a prompt might be: "Show how to generate product suggestions that increase emotional satisfaction using the user's past purchase history and real-time sentiment data."

[0624] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0625] Step 1:

[0626] Users input their personal achievements, history, and interests using devices such as smartphones and tablets. In addition, an emotion engine analyzes the user's facial expressions and voice in real time through the device's camera and microphone to acquire emotional information. The input information is converted into a data format and prepared.

[0627] Step 2:

[0628] The device transmits the converted personal and emotional information to the cloud server according to an encryption protocol. Encryption technologies such as TLS (Transport Layer Security) are used in this process. The input is encrypted data, and the output is a secure data transfer to the server.

[0629] Step 3:

[0630] The server processes the received linked data using an analysis device to analyze user characteristics and aptitudes. First, a machine learning algorithm analyzes the dataset, evaluating multiple parameters to recognize patterns. This highlights characteristics related to the user's emotional responses.

[0631] Step 4:

[0632] Based on the analysis results, the server utilizes a generative AI model to design emotionally satisfying educational options, career choices, or purchasing experiences. Here, prompts are used specifically to guide the model and generate personalized recommendations. The input is the analyzed data, and the output is personalized recommendations.

[0633] Step 5:

[0634] The server delivers the generated career plans and purchase suggestions via the user's smart device or other output devices. This includes methods of providing information in a user-friendly format using notification systems and API interfaces. For example, execution in a SmartView app is being considered.

[0635] Step 6:

[0636] The user receives the presented information and makes a decision based on it. Based on these results, the server collects feedback and continuously trains the model to improve the accuracy of future suggestions. The input is the user's choice feedback, and the output is the enhanced AI model.

[0637] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0638] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0639] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0640] [Fourth Embodiment]

[0641] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0642] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0643] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0644] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0645] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0646] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0647] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0648] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0649] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0650] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0651] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0652] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0653] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0654] This invention is a system that proposes career paths and educational options suitable for individuals, and includes an input device, a data analysis device, a career proposal generation device, and an output device.

[0655] First, the user enters their academic record, activity history, and areas of interest into the input device. The terminal is designed to convert this information into the appropriate data format, encrypt it, and send it to the server.

[0656] The server analyzes the received data using an analysis device to identify the user's characteristics and aptitudes. This analysis uses machine learning algorithms and other methods to extract patterns from the user's data and reveal features related to the user's abilities and interests.

[0657] Next, the server selects the most suitable educational institutions and occupations for the user based on the analysis results and generates a career plan. The career plan includes potential educational institutions, occupational options, necessary skills, and action plans. This information is formatted and presented to the user through an output device.

[0658] For example, if a user's interest lies in law and their past activity history supports this, the system will suggest legal educational institutions and related career options. In this case, for professions such as lawyer or legal consultant, specific steps to acquire the necessary skills and experience will also be provided.

[0659] Finally, the server performs a long-term career simulation based on the user's choices and presents the scenario to the user. This simulation allows the user to understand how their chosen path will unfold and what challenges and opportunities they will face at each stage of their future career.

[0660] The following describes the processing flow.

[0661] Step 1:

[0662] Users input their academic performance, activity history, and areas of interest into a terminal using an input device. This includes specific school grades, past activities, and areas of current interest.

[0663] Step 2:

[0664] The terminal receives the input information and converts it into a data format. This data is formatted into an easy-to-handle format, and the information is verified and supplemented as needed. Next, the terminal encrypts this data and sends it to the server via secure communication.

[0665] Step 3:

[0666] The server receives and decodes the data sent from the terminal. The received data is stored in a database and preprocessed to make it available for use in subsequent analysis steps.

[0667] Step 4:

[0668] The server uses analytical equipment to analyze data and identify user characteristics and aptitudes. Machine learning algorithms are applied to evaluate suitable fields and potential career paths based on the input information.

[0669] Step 5:

[0670] Based on the analysis results, the server generates educational options, occupations, and career plans tailored to the user's interests and characteristics. These plans include detailed information on recommended educational institutions, suitable occupations, and necessary skill sets.

[0671] Step 6:

[0672] The server formats the generated carrier plan and sends it to the device in an easy-to-understand format. The device receives this information and displays it visually to the user.

[0673] Step 7:

[0674] Users review the carrier plans displayed on their devices and make selections based on their interests and preferences. They clarify their expectations and concerns regarding the selected plan.

[0675] Step 8:

[0676] The server runs a long-term career simulation based on the user's choices. This simulation presents the future development and specific steps toward realizing the chosen path.

[0677] Step 9:

[0678] The server sends the simulation results to the terminal and presents the user with future career scenarios. The user can then use this as a reference to develop a concrete action plan.

[0679] (Example 1)

[0680] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0681] Conventional career planning systems merely presented standard plans without adequately considering individual characteristics and aptitudes. Therefore, they failed to support users in choosing the most suitable educational institutions or careers, making it difficult to maximize individual potential. This invention aims to provide more appropriate and specific career plans by analyzing diverse individual data.

[0682] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0683] In this invention, the server includes means for acquiring personal data from an information input device, converting it into a standard data format, and transmitting it; means for analyzing the characteristics of the received personal data using a machine learning algorithm to identify aptitudes; and means for selecting educational institutions and professional occupations based on the analyzed characteristics and aptitudes. This makes it possible to propose specific and practical career plans tailored to each individual user.

[0684] "Personal data" refers to information about an individual, including academic performance, activity history, and areas of interest.

[0685] An "information input device" refers to a device or interface used to acquire personal data, such as a computer input form or a scanner.

[0686] "Converting to a data format" means representing acquired data in a standard form, such as converting it to formats like JSON or XML.

[0687] A "machine learning algorithm" refers to a computational method for finding patterns in large amounts of data and making predictions or decisions based on those patterns.

[0688] "Analyzing characteristics and identifying aptitudes" is the process of using an individual's data to analyze their characteristics and qualities, and to reveal their individual abilities and aptitudes.

[0689] "Selecting educational institutions and professional occupations" refers to determining the most suitable learning environment and occupational position for an individual based on their analyzed characteristics and aptitudes.

[0690] A "career plan" is a plan that outlines the career direction and specific steps an individual should take to achieve their future.

[0691] This invention is a system for proposing a career plan tailored to an individual, and a specific embodiment thereof is shown here.

[0692] Users first input their data using an information input device. This data consists of academic performance, activity history, and areas of interest. The information input device typically involves computer input forms or scanners.

[0693] The terminal converts the acquired data into a standard data format. Specifically, formats such as JSON and XML are used, and data integrity checks and encryption are performed. For encryption, data security is ensured by using methods such as AES encryption. After that, the terminal sends the encrypted data to the server.

[0694] The server executes machine learning algorithms to analyze the received data. This analysis utilizes programming languages ​​such as Python and R, employing algorithms like the randomized forest algorithm and SVM (Support Vector Machine). This allows for the identification of individual user characteristics and aptitudes.

[0695] Based on the analysis results, the server selects the most suitable educational institutions and professional occupations for the user. In this selection process, the server refers to information in the database and lists career options that match the user's characteristics. As a result, a career plan is proposed to the user, providing information on necessary skills and qualifications to acquire.

[0696] Furthermore, the server simulates future activity scenarios based on the career plan selected by the user. This simulation takes into account economic indicators and industry trends related to the user's chosen path to predict future possibilities and risks.

[0697] For example, if a user is interested in the legal field, the system will suggest legal educational institutions and professions (e.g., lawyers or legal consultants) to that user. Specific guidance will also be provided regarding the qualifications and skills necessary for the user to pursue a legal career.

[0698] A concrete example of a prompt used in a generative AI model would be, "Please write a program that proposes the optimal career plan for a student who is interested in the field of law and aspires to become a lawyer."

[0699] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0700] Step 1:

[0701] Users input their academic performance, activity history, and areas of interest into an information input device. The input data is retrieved in text and numerical format and sent to the terminal. The output here is a collection of the data provided by the user.

[0702] Step 2:

[0703] The terminal converts the data received from the user into a standard format (e.g., JSON). At this stage, it performs a data integrity check to ensure there are no missing or abnormal values. After verification, the converted data is secured using AES encryption. The output is encrypted data, which is then sent to the server.

[0704] Step 3:

[0705] The server decrypts the encrypted data received from the terminal and performs analysis using a data analysis device. Here, machine learning algorithms (e.g., randomized forests, SVM) are used to extract patterns for identifying user characteristics and aptitudes. The input is the decrypted data, and the output is the characteristic and aptitude profile obtained through the analysis.

[0706] Step 4:

[0707] The server selects the most suitable educational institutions and professional occupations for the user based on the obtained profile. This process searches an internal database to identify candidates that match the analyzed characteristics and aptitudes. The input is the characteristics and aptitude profile, and the output is a list of selected career options.

[0708] Step 5:

[0709] The server constructs a career plan based on the selected career options. This plan details the proposed educational institutions and the skills and qualifications required for the chosen occupation. Furthermore, this plan serves as the basis for simulating the user's future career. The input is a list of career options, and the output is a detailed career plan.

[0710] Step 6:

[0711] The server runs a simulation of future activities based on the career plan. The simulation considers economic indicators and industry trends to predict the risks and possibilities of the career path chosen by the user. The input is the career plan, and the output is a report of the simulation results.

[0712] Step 7:

[0713] The server formats the simulation results and presents them to the user via the terminal. Through the visualized report on the screen, the user can gain a deeper understanding of their career options. The input is the simulation results, and the output is a visual report to the user.

[0714] (Application Example 1)

[0715] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0716] A challenge in providing optimal recommendations for individual career choices and educational selections is the difficulty in basing them on each individual's characteristics, aptitudes, and interests. Such recommendations need to consider not only past achievements but also current interests and future trends. Furthermore, instead of simply providing information in a one-way manner, it is necessary to obtain more precise information through dialogue with the individual and provide individually optimized recommendations.

[0717] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0718] In this invention, the server includes means for acquiring personal information from an input device, converting it into a data format, and transmitting it; means for analyzing the characteristics of the received personal information with an analysis device and identifying aptitudes; means for selecting educational institutions and occupations based on the analyzed characteristics and aptitudes; means for acquiring information through dialogue with the individual using a speech recognition device; and means for converting the voice input from the individual into text data and storing it in a database. This enables data collection through precise dialogue and highly adapted career proposals.

[0719] An "input device" is hardware or an interface for acquiring personal information, which allows a user to input their own data into the system.

[0720] An "analysis device" is hardware or software used to process received personal information and analyze its characteristics and aptitudes.

[0721] "Aptitude" refers to the abilities and tendencies that are suited to a particular school or occupation, based on an individual's characteristics and interests.

[0722] A "career plan" is a plan based on analysis results that includes the most suitable educational institution and occupational choice for an individual, and details the necessary skills and steps.

[0723] A "speech recognition device" is a device that converts an individual's voice into digital data and understands its content, and is part of an interactive interface.

[0724] "Voice input" refers to voice information emitted by an individual, and serves as a data source for a system to understand and process it.

[0725] A "database" is a collection of information that stores analyzed voice input data and personal information, and is used for later reference and processing.

[0726] The system for realizing this application consists of multiple devices and software to suggest the most suitable career path for an individual. First, the user uses an input device to enter their own information, such as academic performance, activity history, and interests. This input device includes smartphones and personal computers.

[0727] The terminal converts this information into an appropriate data format and sends it to the server via secure communication. Upon receiving this transmitted data, the server uses an analysis device to analyze the data and identify the user's characteristics and aptitudes. This analysis utilizes pattern recognition technology using machine learning algorithms, specifically leveraging libraries such as TensorFlow and scikit-learn.

[0728] Furthermore, the server also collects information from interactions with the user using a speech recognition device. This interaction utilizes speech recognition software such as Google Cloud Speech-to-Text. The user's voice input is converted to text and stored in the system's database.

[0729] Based on the analysis results, the server selects suitable educational institutions and occupations for the user and generates a career plan. This includes multiple options tailored to the user's interests and analyzed characteristics. This information is formatted and presented to the user through an output device. The optimal career path proposal also includes long-term simulations tailored to the user's preferences, and the accuracy of the simulations is enhanced using cloud computing resources from Azure and AWS.

[0730] For example, if a user expresses interest in "law" and their past activities support this, the system will suggest law-related educational institutions and careers. For instance, it might suggest specific steps to pursue law school or become a legal professional.

[0731] An example of a prompt message would be: "Generate future career options based on the user's interests and past work experience. For example, if the user is interested in law, suggest related career paths."

[0732] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0733] Step 1:

[0734] Users input their academic records, activity history, and areas of interest using an input device. The entered data is converted into the appropriate data format via an application used on a smartphone or personal computer. This data is encrypted by the device and transmitted to the server in a secure manner.

[0735] Step 2:

[0736] The server passes the received data to the analysis device and begins data analysis. The input data includes numerical and text data, and machine learning algorithms are used to identify user characteristics and aptitudes during the analysis. Specific data processing includes normalization and one-hot encoding, resulting in the output of a vector representing user characteristics.

[0737] Step 3:

[0738] The server activates the speech recognition device and collects additional information through interaction with the user. The speech data is converted into text data in real time and stored in a database. This text data is used for analysis as supplementary data to understand the user's interests and emotions.

[0739] Step 4:

[0740] Based on the analysis results, the server selects educational and career options optimized for the user. This involves using a generative AI model, taking previously generated characteristic vectors and data supplemented by speech recognition as input, to generate career choices. These generated career options are then output as a set of recommendations based on the user's potential.

[0741] Step 5:

[0742] The server creates a detailed career plan based on the selected educational institution and occupation. This plan includes necessary skills and action steps, providing the user with concrete guidance. After formatting adjustments, the generated plan is presented to the user through an output device.

[0743] Step 6:

[0744] Depending on the user's selection, the server performs long-term simulations and provides a virtual scenario showing how that career choice will unfold. This simulation leverages cloud computing resources and outputs a detailed outlook on future challenges and opportunities.

[0745] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0746] This invention provides a system that utilizes emotional information in addition to personal information of users to propose more sophisticated career plans. The system includes an input device, an emotional engine, a data analysis device, a career proposal generation device, and an output device.

[0747] First, as the user inputs their academic performance, activity history, and areas of interest into the terminal via an input device, the emotion engine recognizes the user's emotions in real time. The terminal converts this information into a data format, encrypts it, and sends it to the server.

[0748] The server analyzes both the received personal data and emotional data using an analysis device to identify the user's characteristics and aptitudes. This analysis takes into account the emotional data provided by the emotion engine, reflecting, for example, the emotional responses a user has to a particular field of study or occupation, enabling a more individualized and accurate analysis.

[0749] Based on the analysis results, the server selects the most suitable educational institutions and occupations for the user. This selection also takes emotional compatibility into account, creating a career path that is likely to be emotionally satisfying for the user. In particular, by predicting long-term emotional changes and reflecting them in the career simulation, suggestions are made to enhance future satisfaction and happiness.

[0750] For example, if a user is interested in healthcare but the emotion engine detects that they are likely to experience psychological stress, the server will also suggest occupations that require similar skills but involve less psychological stress. In this way, the system presents educational options and occupations that are suitable for the user's emotional needs and offers them to the user via an output device.

[0751] Ultimately, the server sends simulation results and career plans to the terminal, allowing the user to plan their future based on the presented information. In this way, by combining emotional information, this system provides more beneficial and personalized suggestions to the user than existing career support systems.

[0752] The following describes the processing flow.

[0753] Step 1:

[0754] Users input their academic performance, activity history, and areas of interest into an input device. This includes grades in specific subjects, club activities participated in, and hobbies.

[0755] Step 2:

[0756] The device receives input from the user, and simultaneously, an emotion engine analyzes the user's facial expressions and voice to recognize the emotion at the time of input. This emotion data, along with the input information, is converted into a data format and sent to the server in an encrypted form.

[0757] Step 3:

[0758] The server processes personal information and emotional data received from the terminal using an analysis device. First, the data is decoded, and then analysis including emotional data is performed to identify the user's characteristics and aptitudes. At this stage, emotional data is taken into account to calculate, for example, an emotional prediction regarding areas of interest.

[0759] Step 4:

[0760] Based on the analysis results, the server takes feedback from the emotion engine into consideration when selecting schools or careers. It not only assesses aptitude and characteristics, but also forms options that are likely to emotionally satisfy the user.

[0761] Step 5:

[0762] The server generates a career plan that reflects emotional compatibility, incorporating specific actions such as required skills, experience, and recommended activities. This provides a career plan that is emotionally harmonious.

[0763] Step 6:

[0764] The server formats the generated carrier plan and sends it to the terminal. The terminal then presents the received information to the user in a visually easy-to-read format.

[0765] Step 7:

[0766] Users review the presented career plans, evaluate them, and make choices that match their desires and feelings.

[0767] Step 8:

[0768] The server runs a long-term career simulation based on the user's chosen career path, taking into account emotional changes. This simulation predicts the emotional impact of the chosen path and emotional adaptation, and uses the results to make suggestions that can increase user satisfaction.

[0769] Step 9:

[0770] The server sends the simulation results and final career plan to the terminal, which then presents them to the user. Based on this information, the user can then concretize and proceed with their actual action plan.

[0771] (Example 2)

[0772] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0773] Traditional career planning systems have suggested educational institutions and occupations based on individual attribute information, but they do not consider emotional information, making it difficult to provide suggestions that adequately consider the user's long-term satisfaction and suitability. Furthermore, they have been unable to provide plans that take into account the user's emotional fit to specific academic fields or occupations. Ultimately, there is a need for suggestions that aim to ensure users are emotionally satisfied with their chosen path and occupation.

[0774] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0775] In this invention, the server includes means for acquiring an individual's attributes from an input mechanism and converting them into a data structure, means for collecting emotional information at the time of input, and means for comprehensively analyzing the received individual's attributes and emotional information with an analysis device to identify characteristics and aptitudes. This makes it possible to suggest educational institutions and occupations that take into account the user's emotional compatibility and satisfaction.

[0776] "Personal attributes" refer to information about an individual, including their academic performance, activity history, and areas of interest.

[0777] An "input mechanism" refers to a device or means used by a user to input personal attributes into a terminal.

[0778] "Converting to a data structure" refers to converting acquired personal attribute and sentiment information into a format that can be processed by a computer (e.g., JSON or XML).

[0779] An "emotion recognition mechanism" refers to a technology or device that identifies and collects information about a user's emotions in real time during input.

[0780] An "analysis device" refers to a computer system used to analyze a user's characteristics and aptitudes using received personal attribute and emotional information.

[0781] "Integrated analysis" refers to a process that simultaneously considers an individual's attributes and emotional information, and then conducts a comprehensive evaluation of them.

[0782] "Identifying characteristics and aptitudes" refers to clarifying the user's characteristics and suitable fields based on analysis.

[0783] "Emotional compatibility" refers to an indicator that shows how emotionally suitable a particular school or occupation is for a user, based on the emotional information they provide.

[0784] "Long-term emotional change" refers to predicting how a user's emotional state will change over time.

[0785] "Career planning" refers to planning future strategies, including suitable educational institutions and occupations, based on analyzed data.

[0786] "Output mechanism" refers to a device or means for presenting analysis results or proposals to the user, and includes displays, printers, and the like.

[0787] This invention comprises a system equipped with a device (input mechanism) for users to input personal attribute information and an emotion recognition mechanism that recognizes emotional information from the user in real time. Users input information such as academic performance, activity history, and areas of interest into the terminal using a keyboard or touchscreen. The terminal converts this data into a format that can be processed by a computer and further collects emotional information via the emotion recognition mechanism. This system may utilize, for example, facial expression recognition software or voice analysis technology.

[0788] Next, the device encrypts this information and securely transmits it to the server. The server comprehensively analyzes the received data using an analysis device and utilizes a generative AI model to identify characteristics, aptitudes, and emotional compatibility. This analysis employs machine learning models and data mining techniques, and more precise analysis is performed by comparing the user's past data with emotional data.

[0789] Based on the analysis results, the server selects the most suitable educational institutions and occupations for the user. This selection also considers the user's emotional compatibility, and a career plan, including simulations, is created to ensure the user can pursue a long-term, satisfying career. The generated career plan is presented to the user via an output mechanism. Output devices such as displays and printers are possible, allowing the user to visually confirm the proposal.

[0790] For example, if a user is interested in engineering but feels anxious about giving presentations, we can suggest an engineering position that involves minimal interpersonal communication and is primarily desk-based. This also helps ensure the user's emotional stability.

[0791] An example of a prompt message would be: "Based on the user's interests and emotional data, please use AI to suggest the optimal career plan. If the user is not good at presentations, please also consider options that involve less interpersonal communication, even if they are technical positions."

[0792] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0793] Step 1:

[0794] Subject: User

[0795] Users input personal attribute information such as academic performance, activity history, and areas of interest into the terminal via an input mechanism. Users input this information using a keyboard or touchscreen. Additionally, the system captures the user's visual and auditory information, and an emotion recognition mechanism identifies the user's emotional state in real time. The input information is sent to the terminal as text data.

[0796] Step 2:

[0797] Subject: Important

[0798] The device integrates personal attribute information entered by the user with sentiment information acquired in real time and converts it into a digital data format (e.g., JSON or XML). This converted data is encrypted as a data stream and sent to the server using a secure protocol (e.g., HTTPS). The transmitted data includes the user's text information and sentiment information.

[0799] Step 3:

[0800] Subject: Server

[0801] The server passes the data received from the terminal to the analysis device. The analysis device uses a generative AI model to analyze the characteristics and suitability of the received data. This process employs machine learning algorithms to perform data analysis that integrates the user's personal attributes and emotional information. This analysis extracts the emotional responses and aptitudes that the user exhibits in specific fields, and generates analysis results.

[0802] Step 4:

[0803] Subject: Server

[0804] The server selects the most suitable educational institutions and occupations based on the analysis results. This selection takes into account the analyzed characteristics, aptitudes, and emotional compatibility. For example, if the analysis reveals that the user feels anxious about presentations, occupations with minimal interpersonal communication will be selected. This generated career plan is output as structured data.

[0805] Step 5:

[0806] Subject: Server

[0807] The generated career plan is presented to the user via an output mechanism. The server displays the information in a visually verifiable format using a display or printer. The user can then consider their own future plans based on this proposal. The generated career plan includes explanations based on the reasons for the proposal and emotional suitability.

[0808] (Application Example 2)

[0809] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0810] Existing career plan proposal systems have limitations in providing personalized suggestions that take into account user emotions. Furthermore, the personalization of the purchasing experience in electronic payment services is insufficient, and there is a need to improve customer satisfaction.

[0811] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0812] In this invention, the server includes means for acquiring personal information and emotional information from an input device, converting it into a data format, and transmitting it; means for analyzing the characteristics of the received personal information and emotional information with an analysis device and identifying aptitudes; means for selecting educational institutions and occupations that take emotional satisfaction into consideration based on the analyzed characteristics and aptitudes; and means for generating personalized purchase suggestions based on emotional information and presenting them via an output device. This makes it possible to propose personalized career plans and optimize the purchasing experience by utilizing the user's emotional information.

[0813] "Personal information" refers to attribute data about the user, such as performance, history, and interests.

[0814] "Emotional information" refers to data that detects and quantifies the user's emotional state in real time.

[0815] An "input device" refers to a device or interface that a user uses to input information.

[0816] "Means of converting and transmitting data" refers to the process of electronically processing input information, converting it to an appropriate format, and sending it to a server.

[0817] An "analysis device" refers to a system that performs analysis based on received information to investigate the user's characteristics and aptitudes.

[0818] "Characteristics" and "aptitudes" refer to attributes and categories based on a user's abilities, personality, and interests.

[0819] "Emotional satisfaction" refers to the emotional fulfillment a user experiences with a particular choice.

[0820] A "career plan" refers to designing a path regarding further education and employment.

[0821] "Purchase suggestions" refer to advice and recommendations for purchases generated based on the user's purchase history and emotional information.

[0822] "Output device" refers to a display or interface used to present generated information to the user.

[0823] This invention is a system that combines users' personal information and emotional information to provide specific and emotionally satisfying career plans and purchase suggestions.

[0824] In this system, users input personal information such as performance, history, and interests using input devices such as smartphones and tablets. Furthermore, a device with a built-in emotion engine analyzes the user's emotions in real time from their facial expressions and voice, and collects data. This emotion analysis uses a camera and microphone, and is implemented with facial recognition software and voice recognition algorithms.

[0825] The acquired information is converted into a data format and sent to a cloud server using encryption technology. Specifically, data transfer protocols and encryption algorithms are responsible for this process. The server utilizes cloud infrastructure such as AWS (Amazon Web Services) to provide secure data storage and powerful analytical capabilities.

[0826] On the server side, powerful data analysis tools integrate personal and emotional information to analyze user characteristics and aptitudes in detail. This analysis uses machine learning algorithms to automatically recognize data patterns, and further optimized career plans and purchase recommendations are generated by generative AI models.

[0827] Based on the analyzed information, the server provides users with educational institutions, career options, or purchasing experiences that are likely to be emotionally satisfying. The selected content is delivered to the user via an output device. For example, the information is displayed on the user's smart TV or mobile device using Samsung's SmartView app.

[0828] As a concrete application example, when a user displays a joyful expression while shopping, new products are recommended in real time based on that history. This creates a shopping experience that enhances user satisfaction.

[0829] An example of a prompt might be: "Show how to generate product suggestions that increase emotional satisfaction using the user's past purchase history and real-time sentiment data."

[0830] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0831] Step 1:

[0832] Users input their personal achievements, history, and interests using devices such as smartphones and tablets. In addition, an emotion engine analyzes the user's facial expressions and voice in real time through the device's camera and microphone to acquire emotional information. The input information is converted into a data format and prepared.

[0833] Step 2:

[0834] The device transmits the converted personal and emotional information to the cloud server according to an encryption protocol. Encryption technologies such as TLS (Transport Layer Security) are used in this process. The input is encrypted data, and the output is a secure data transfer to the server.

[0835] Step 3:

[0836] The server processes the received linked data using an analysis device to analyze user characteristics and aptitudes. First, a machine learning algorithm analyzes the dataset, evaluating multiple parameters to recognize patterns. This highlights characteristics related to the user's emotional responses.

[0837] Step 4:

[0838] Based on the analysis results, the server utilizes a generative AI model to design emotionally satisfying educational options, career choices, or purchasing experiences. Here, prompts are used specifically to guide the model and generate personalized recommendations. The input is the analyzed data, and the output is personalized recommendations.

[0839] Step 5:

[0840] The server delivers the generated career plans and purchase suggestions via the user's smart device or other output devices. This includes methods of providing information in a user-friendly format using notification systems and API interfaces. For example, execution in a SmartView app is being considered.

[0841] Step 6:

[0842] The user receives the presented information and makes a decision based on it. Based on these results, the server collects feedback and continuously trains the model to improve the accuracy of future suggestions. The input is the user's choice feedback, and the output is the enhanced AI model.

[0843] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0844] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0845] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0846] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0847] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0848] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0849] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0850] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0851] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0852] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0853] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0854] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0855] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0856] 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.

[0857] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0858] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0859] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0860] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0861] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0862] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0863] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0864] The following is further disclosed regarding the embodiments described above.

[0865] (Claim 1)

[0866] A means of acquiring personal information from an input device, converting it into a data format, and transmitting it,

[0867] A means of analyzing the characteristics of received personal information using an analysis device to identify suitability,

[0868] Based on the analyzed characteristics and aptitudes, a means for selecting a school or occupation,

[0869] A means of constructing a career plan based on the selected educational institution or occupation and proposing it via an output device,

[0870] A system that includes this.

[0871] (Claim 2)

[0872] The system according to claim 1, further comprising means for performing long-term activity simulations for careers selected based on the proposals made by the aforementioned means.

[0873] (Claim 3)

[0874] The system according to claim 1, wherein the transmitted personal information includes academic performance, activity history, and interest information.

[0875] "Example 1"

[0876] (Claim 1)

[0877] A means of acquiring personal data from an information input device, converting it to a standard data format, and transmitting it,

[0878] A means of analyzing characteristics and identifying suitability by using machine learning algorithms to analyze received personal data,

[0879] Based on the analyzed characteristics and aptitudes, a means for selecting educational institutions and professional occupations,

[0880] A means of constructing a career plan according to selected educational institutions and professional occupations and proposing it via an information output device,

[0881] A system that includes this.

[0882] (Claim 2)

[0883] The system according to claim 1, comprising means for executing future activity scenarios for a career plan selected based on the proposals made by the aforementioned means.

[0884] (Claim 3)

[0885] The system according to claim 1, wherein the transmitted personal data includes academic performance, activity history, and areas of interest.

[0886] "Application Example 1"

[0887] (Claim 1)

[0888] A means of acquiring personal information from an input device, converting it into a data format, and transmitting it,

[0889] A means of analyzing the characteristics of received personal information using an analysis device to identify suitability,

[0890] Based on the analyzed characteristics and aptitudes, a means for selecting a school or occupation,

[0891] A means of constructing a career plan based on the selected educational institution or occupation and proposing it via an output device,

[0892] A means of acquiring information through dialogue with an individual using a speech recognition device,

[0893] A means for converting the voice input from the aforementioned individual into text data and storing it in a database,

[0894] A system that includes this.

[0895] (Claim 2)

[0896] The system according to claim 1, further comprising means for performing long-term activity simulations for careers selected based on the proposals made by the aforementioned means.

[0897] (Claim 3)

[0898] The system according to claim 1, wherein the transmitted personal information includes academic performance, activity history, and interest information, as well as information obtained through voice interaction.

[0899] "Example 2 of combining an emotion engine"

[0900] (Claim 1)

[0901] A means of obtaining individual attributes from an input mechanism and converting them into a data structure,

[0902] It includes an emotion recognition mechanism that identifies emotions in real time, and means for collecting emotion information at the time of input,

[0903] Means for securely transmitting the converted data and emotional information through a communication device,

[0904] A means for comprehensively analyzing received personal attribute and emotional information using an analysis device to identify characteristics and aptitudes,

[0905] A means of selecting educational institutions and jobs based on analyzed characteristics, aptitudes, and emotional compatibility,

[0906] A means of conducting career simulations that take long-term emotional changes into account, designing career plans, and proposing them through an output mechanism,

[0907] A system that includes this.

[0908] (Claim 2)

[0909] The system according to claim 1, further comprising means for performing a simulation to predict emotional compatibility and satisfaction with the career path selected based on the proposal by the aforementioned means.

[0910] (Claim 3)

[0911] The system according to claim 1, wherein the attributes of the individual transmitted include academic performance, activity history, and areas of interest.

[0912] "Application example 2 when combining with an emotional engine"

[0913] (Claim 1)

[0914] A means of acquiring personal information and emotional information from an input device, converting it into a data format, and transmitting it,

[0915] A means of identifying aptitudes by analyzing the characteristics of received personal information and emotional information using an analysis device,

[0916] Based on the analyzed characteristics and aptitudes, a means for selecting educational institutions and occupations that take emotional satisfaction into consideration,

[0917] A means of constructing a career plan based on the selected educational institution or occupation and proposing it via an output device,

[0918] A means for generating personalized purchase suggestions based on emotional information and presenting them via an output device,

[0919] A system that includes this.

[0920] (Claim 2)

[0921] The system according to claim 1, further comprising means for performing activity simulations that take into account long-term emotional changes for a career selected based on the proposal by the aforementioned means.

[0922] (Claim 3)

[0923] The system according to claim 1, wherein the personal information transmitted includes achievements, history, and interests. [Explanation of Symbols]

[0924] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of acquiring personal information from an input device, converting it into a data format, and transmitting it, A means of analyzing the characteristics of received personal information using an analysis device to identify suitability, Based on the analyzed characteristics and aptitudes, a means for selecting a school or occupation, A means of constructing a career plan based on the selected educational institution or occupation and proposing it via an output device, A means of acquiring information through dialogue with an individual using a speech recognition device, A means for converting the voice input from the aforementioned individual into text data and storing it in a database, A system that includes this.

2. The system according to claim 1, further comprising means for performing long-term activity simulations for careers selected based on the proposals made by the aforementioned means.

3. The system according to claim 1, wherein the transmitted personal information includes academic performance, activity history, and interest information, as well as information obtained through voice interaction.

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