System

Abstract

A system is provided.SOLUTION: An input unit configured to input job information provided by a company, an analysis unit including artificial intelligence configured to analyze the input job information and decompose the input job information into a plurality of individual tasks, a storage unit configured to store the analyzed individual tasks and conditions related to the individual tasks in a database, an input unit configured to input an ability and a limitation of a user, a storage unit configured to store the input ability and limitation information of the user in the database, the system includes a collation means for generating optimum job matching and a notification means for notifying the company and the user of a collation result.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] It is difficult to achieve appropriate job matching between companies and people with disabilities. Specifically, the job information provided by companies is abstract, making it difficult for people with disabilities to choose jobs based on their own abilities. Furthermore, because the abilities and limitations of people with disabilities are not fully understood, appropriate job matching is not possible, resulting in a low employment rate for people with disabilities and a high turnover rate. [Means for solving the problem]

[0005] The present invention provides a system including an input means for inputting job information provided by a company, an analysis means including artificial intelligence for analyzing the input job information and breaking it down into multiple individual tasks, a storage means for saving the analyzed individual tasks and their associated conditions in a database, an input means for a user to input their own abilities and limitations, a storage means for saving the input user's ability and limitation information in the database, a comparison means for comparing the saved job information with user information to generate optimal job matching, and a notification means for notifying the company and user of the comparison result. This system allows the company's job information to be broken down in detail and the abilities and limitations of people with disabilities to be accurately identified, thereby enabling more appropriate job matching.

[0006] An "enterprise" is a legal entity or sole proprietorship that provides services or products.

[0007] "Job information" refers to information provided by a company, including job content, responsibilities, and required skills and conditions.

[0008] "Input means" refers to an interface for inputting job information and user information into the system, and includes a keyboard, touch screen, voice input, etc.

[0009] "Analysis means" refers to a method, including artificial intelligence and natural language processing technology, for analyzing input information and breaking it down into multiple individual tasks.

[0010] An "individual task" is a unit of work or individual tasks that make up an entire job.

[0011] "Conditions" are the skills, abilities, or environmental requirements necessary to perform an individual task.

[0012] The "storage means" is a mechanism for storing analyzed information and input information in a database or the like.

[0013] A "user" is a person who tries to check the suitability of his or her own abilities for a job based on job information.

[0014] "Ability" refers to the tasks a user can perform and the skills they possess.

[0015] A "limitation" is a physical, environmental, or other constraint that a user faces when performing a particular task.

[0016] The "matching means" is a system function that compares the saved job information with the user information and generates the optimal match.

[0017] "Notification means" refers to the method and system for communicating matching results to companies and users. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9]1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] The present invention is a system that realizes optimal job matching by analyzing job information provided by companies and breaking it down into tasks that can be performed by people with disabilities. Specific embodiments of the system are described below.

[0040] Overall system overview

[0041] The system consists of the following main functions:

[0042] 1. Entering and analyzing job information

[0043] 2. Input of the abilities and limitations of the person with a disability

[0044] 3. Job matching generation and notification

[0045] 1. Entering and analyzing job information

[0046] Company processing

[0047] Terminal: Provides a form for company recruiters to enter job details in natural language, including a job summary, specific job duties, and required skills and qualifications.

[0048] Server: Once job information is input, it uses natural language processing (NLP) algorithms and machine learning models to analyze it, which breaks it down into multiple specific tasks.

[0049] Server: Each decomposed task and its associated conditions (e.g., physical conditions and skill requirements) are stored in a database.

[0050] Examples:

[0051] When a company recruiter inputs "store management, purchasing management, and staff shift management," the AI ​​analyzes this and breaks it down into tasks such as "inventory management," "customer service," and "sales management." Each task is assigned a requirement such as "basic arithmetic ability" and "interpersonal skills."

[0052] 2. Input of the abilities and limitations of the person with a disability

[0053] Processing for people with disabilities

[0054] Device: Provides a checklist-style form for people with disabilities to enter their capabilities and limitations, including tasks they can perform and conditions they cannot accommodate.

[0055] Server: The information entered is stored in a database as a user profile.

[0056] Examples:

[0057] When a person with a disability enters "Tasks they can do: plating food," "Tasks they cannot do: carrying heavy objects," and "Restrictions: using a wheelchair," that information is saved in a database.

[0058] 3. Job matching generation and notification

[0059] Matching process

[0060] Server: Matches the job details table with the user profile table and generates matching candidates based on matching tasks and conditions.

[0061] Server: Calculates the matching score and generates the best job matching based on it. The matching score is determined by the compatibility of the task and the user's skills and constraints.

[0062] Server: Stores the matching results in a database and notifies companies and people with disabilities of the results.

[0063] Examples:

[0064] The server compares the tasks of "plating" and "washing dishes" with job ID 1234 with the profile of user ID 5678 and calculates a matching score. If the score is 85, the result is saved in the database and notified to the company and the person with a disability.

[0065] Checking the results

[0066] Device: Company recruiters and people with disabilities can view matching results on their dashboards.

[0067] On your device: The dashboard displays your matches and their matching scores.

[0068] In this way, this system analyzes companies' job information in detail and matches jobs that suit the abilities and limitations of people with disabilities, aiming to increase employment opportunities for people with disabilities and reduce turnover rates.

[0069] The processing flow will be explained below.

[0070] Step 1:

[0071] User: A company's recruiter enters job information in natural language into the automated job decomposition system's input form. This information includes a job summary, specific job duties, and required skills and conditions.

[0072] Step 2:

[0073] Server: Receives input job information and passes it to a natural language processing (NLP) algorithm, which parses the job information and breaks it down into multiple individual tasks based on templates.

[0074] Step 3:

[0075] Server: The server uses machine learning models to refine the analyzed tasks and estimate the requirements for each task (e.g., specific skills or physical abilities). This determines the requirements for each task.

[0076] Step 4:

[0077] Server: Stores the decomposed tasks and their associated condition information in the task details table for later collation and matching.

[0078] Step 5:

[0079] User: A person with a disability enters information about the tasks and limitations they can perform in the form of a checklist. The checklist lists specific tasks and limitations, and the user selects which ones they can perform.

[0080] Step 6:

[0081] Server: Receives the information entered by the person with a disability and stores it in a user profile table, including the tasks they can perform and their limitations.

[0082] Step 7:

[0083] Server: Checks the stored job details table against the user profile table to perform appropriate job matching, specifically checking whether the task content and conditions match the user's available tasks and restrictions.

[0084] Step 8:

[0085] Server: Calculates a matching score based on the compatibility between the job and the user. The matching score is determined by the degree to which each task matches the user's skills and constraints.

[0086] Step 9:

[0087] Server: Saves the matching results, including the matching score, in a matching table and notifies companies and people with disabilities of the results. The optimal matching information for each user and job is provided.

[0088] Step 10:

[0089] Users: Company recruiters view the matching results through a dedicated dashboard, which displays a list of matching candidates and each candidate's matching score.

[0090] Step 11:

[0091] Users: People with disabilities can check their matching results through a dedicated dashboard, which displays a list of jobs that have been matched to them and their matching scores.

[0092] Through these steps, detailed job matching will be carried out between companies and people with disabilities, providing more appropriate employment opportunities.

[0093] Example 1

[0094] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0095] In recent years, companies have been providing a wide variety of job information, but it is difficult for people with disabilities to find tasks that they can perform appropriately. It is also difficult for people with disabilities themselves to find jobs that suit their abilities and limitations, which reduces employment opportunities and contributes to high turnover rates. Current systems often lack sufficient analysis of job information and do not properly generate or match task lists suitable for people with disabilities. Therefore, there is a need for an effective system that allows people with disabilities to find jobs that suit them and companies to hire the right personnel.

[0096] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0097] In this invention, the server includes an input means for inputting job information provided by a company, an analysis means including artificial intelligence for analyzing the input job information and breaking it down into multiple individual tasks, a storage means for saving the analyzed individual tasks and their associated conditions in a database, an input means for a user to input their own abilities and limitations, a storage means for saving the input user ability and limitation information in the database, a comparison means for comparing the saved job information with user information to generate optimal job matching, a notification means for notifying the company and user of the comparison results, and a display means for displaying the comparison results on a dashboard. This enables detailed analysis of company job information and job matching that is appropriate for the abilities and limitations of people with disabilities.

[0098] "Company" refers to an organization that provides job information and conducts recruitment activities.

[0099] "Job information" refers to information provided by companies, such as job content, required skills, conditions, etc.

[0100] "Input means" refers to an interface through which a user inputs text and options.

[0101] The "analysis means" is a system that uses artificial intelligence to analyze input job information and break it down into multiple individual tasks.

[0102] "Artificial intelligence" is a technology that uses natural language processing and machine learning models to analyze and classify data.

[0103] "Storage means" refers to a system that stores analyzed data and input information in a database.

[0104] "User" refers to a person with a disability who uses the system.

[0105] "Ability" refers to the tasks a user can perform and the skills they possess.

[0106] "Limitations" refers to constraints such as tasks that a user cannot perform or physical conditions that the user has.

[0107] The "matching means" is a system that generates optimal job matching based on the stored job information and user information.

[0108] "Notification means" is a system for notifying companies and users of the matching results.

[0109] A "display means" is a system that visually displays information to a user through an interface such as a dashboard.

[0110] The present invention is a system that realizes optimal job matching by analyzing job information provided by companies and breaking it down into tasks that can be performed by people with disabilities. Specific embodiments of the system are described below.

[0111] System Overview

[0112] The system consists of the following main hardware and software components:

[0113] Devices: Computers, smartphones, or other devices used by company recruiters and people with disabilities to enter information.

[0114] Server: A computer system that analyzes input data and stores, collates, and notifies users. Specific examples include Apache and Nginx servers.

[0115] Database: A database system for storing analyzed job information and user profiles. Specific examples include MySQL and PostgreSQL.

[0116] Artificial intelligence models: Natural language processing (NLP) algorithms and machine learning models used to parse job information and break it down into tasks. Specific examples include Python's NLTK, SpaCy, TensorFlow, and Scikit-learn.

[0117] Specific processing flow

[0118] 1. Entering and analyzing job information

[0119] Terminal: A company's recruiter enters job details into an input form, which includes a job summary, specific job duties, and required skills and conditions.

[0120] Example: A recruiter enters "store management, purchasing management, staff shift management."

[0121] Server: Once job information is entered, it is analyzed using natural language processing (NLP) algorithms and machine learning models. As a result of the analysis, the job information is broken down into multiple specific tasks.

[0122] Example: The server breaks down job information into tasks such as "inventory management," "customer support," and "sales management."

[0123] Server: Each decomposed task and its associated conditions (e.g., physical conditions and skill requirements) are stored in a database.

[0124] 2. Input of the abilities and limitations of the person with a disability

[0125] Device: People with disabilities enter their capabilities and limitations using a checklist-style form, which lists the tasks they can perform and the conditions they cannot accommodate.

[0126] Example: A person with a disability enters "Tasks I can do: Placing food on the table," "Tasks I cannot do: Carrying heavy objects," and "Restrictions: Using a wheelchair."

[0127] Server: The entered information is stored in a database as a user profile.

[0128] 3. Job matching generation and notification

[0129] Server: Compares the job details table with the user profile table and generates matching candidates based on compatible tasks and conditions. Specifically, it uses natural language processing and machine learning models to calculate the compatibility between tasks and user profiles.

[0130] Example: The server matches the "plating" task with the user's profile and calculates a matching score.

[0131] Server: Generates optimal job matches based on the matching scores, stores the results in a database, and notifies companies and people with disabilities of the results.

[0132] 4. Check the results

[0133] Device: Corporate recruiters and people with disabilities can check their matching results on their own dashboard.

[0134] Example: Companies and people with disabilities evaluate the matching results confirmed through the dashboard and take the following actions:

[0135] Prompt Sentence Examples

[0136] Analyze job information entered by companies, break it down into specific tasks, and compare it with the abilities and limitations entered by individuals with disabilities to generate an appropriate job matching score.

[0137] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0138] Step 1:

[0139] The terminal provides an input form for company recruiters to enter job details. The recruiter inputs the job summary, specific work content, required skills and conditions in natural language. This input sends the job information to the server. Input data includes "store management, purchasing management, staff shift management," etc.

[0140] Step 2:

[0141] The server stores the received job information in a temporary database, which is used for later analysis. The stored data is the entire job information entered.

[0142] Step 3:

[0143] The server begins to analyze the stored job information. Using natural language processing (NLP) algorithms (such as Python's NLTK or SpaCy) and machine learning models (such as TensorFlow or Scikit-learn), it analyzes the job information and breaks it down into multiple specific tasks. The input data is the entire job information, and the output data is the broken down task list and corresponding conditions. For example, the job information is broken down into the tasks "inventory management," "customer support," and "sales management."

[0144] Step 4:

[0145] The server stores each decomposed task and its associated conditions in a database. The stored data includes detailed information about each task (e.g., "basic arithmetic ability" for "inventory management" and "interpersonal skills" for "customer service").

[0146] Step 5:

[0147] The device provides a checklist-style input form for people with disabilities to enter their abilities and limitations. People with disabilities enter the tasks they can do and the conditions they cannot handle. This input creates a user profile, which is sent to the server. Input data includes such things as "Tasks they can do: plating food," "Tasks they cannot do: carrying heavy objects," and "Limitations: using a wheelchair."

[0148] Step 6:

[0149] The server stores the data received from the disabled person in a temporary database, which is later used for matching purposes. The stored data is the entire entered user profile.

[0150] Step 7:

[0151] The server compares the saved job information with the user profile and generates matching candidates based on compatible tasks and conditions. This uses natural language processing and machine learning models, with the input data being the job details table and user profile table, and the output data being the matching candidates. The server calculates the compatibility between the task and the user's skills and restrictions, and calculates a matching score. As a specific example, the task "plating" is compared with the user's profile, and the matching score is calculated as 75 points.

[0152] Step 8:

[0153] The server stores the matching results in a database and notifies the company and the person with a disability of the results. The stored data is the matching score and the corresponding task list, and the notification includes the job ID, user ID, and compatibility score.

[0154] Step 9:

[0155] The device provides an interface for corporate recruiters and people with disabilities to check matching results on their own dashboards. The data displayed is the matched candidates and their matching scores. For example, the dashboard might show that "User ID 5678 matches Job ID 1234 with a matching score of 75."

[0156] (Application example 1)

[0157] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0158] Previously, there were systems that analyzed job information provided by companies and matched them with tasks suitable for people with disabilities, but these systems did not support real-time task notifications or execution support, making it difficult for people with disabilities to continuously perform appropriate tasks at work sites such as logistics centers.In addition, people with disabilities could not easily recognize or understand the optimal tasks according to their own situation, making it difficult to increase employment opportunities and achieve efficient work.

[0159] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0160] In this invention, the server includes: an input means for inputting job information provided by a company; an analysis means including artificial intelligence for analyzing the input job information and breaking it down into multiple individual tasks; a storage means for saving the analyzed individual tasks and their associated conditions in a database; an input means for a user to input their own abilities and limitations; a storage means for saving the input user ability and limitation information in the database; a matching means for collating the saved job information and user information to generate optimal job matching; a notification means for notifying the company and the user of the matching results; and a head-mounted display including a display device for displaying the notified tasks in real time and supporting their completion. This enables people with disabilities at logistics centers to recognize and appropriately complete the tasks that are optimal for them in real time.

[0161] An "enterprise" is an organization that conducts business, such as a company or corporation.

[0162] "Job information" refers to information provided by a company, such as the business content, job details, required skills and conditions, etc.

[0163] "Input means" means a device or software for inputting information into a system.

[0164] "Analysis means" refers to a device or software that breaks down input information and extracts meaning.

[0165] "Artificial intelligence" is a technology that uses machine learning and natural language processing to analyze data and solve problems.

[0166] "Storage means" refers to a device or software for storing data for a certain period of time.

[0167] A "database" is a system for efficiently storing, managing, and searching data.

[0168] "User" refers to any person, including a person with a disability, who uses the system and receives tasks.

[0169] "Ability" refers to the skills and tasks that a user can perform.

[0170] "Limitations" refer to skills or tasks that a user cannot perform.

[0171] The "matching means" refers to a device or software that compares the stored job information with the user information and derives the optimal match.

[0172] "Notification means" means a device or software for notifying users of match results or other information.

[0173] A "head-mounted display" is a device worn on the head to display information.

[0174] "Real-time" refers to processing and information exchange occurring instantly with little or no delay.

[0175] Overall system overview

[0176] This invention is a system for efficiently matching tasks for people with disabilities in logistics centers. The system inputs and analyzes job information, inputs the abilities and limitations of people with disabilities, generates and notifies job matching, and provides real-time task notification and execution support.

[0177] 1. Entering and analyzing job information

[0178] The company's terminal has an input means for entering job information. The entered job information is analyzed by the server. Natural language processing (NLP) and machine learning models are used for the analysis. This breaks down the job information into multiple individual tasks. The analyzed tasks and their associated conditions are stored in a database by the server.

[0179] For example, if a company recruiter inputs "stock organization, packing, and product movement," the AI ​​will break this down into "inventory management," "packing work," and "transportation work." Each task will be assigned a condition such as "basic arithmetic ability" or "manual dexterity."

[0180] 2. Input of the abilities and limitations of the person with a disability

[0181] The device on the disabled person's side has a checklist-style input means for entering their abilities and limitations. The input information is saved in a database as a user profile, which clarifies the tasks that the disabled person can perform and their limitations.

[0182] For example, if a person with a disability enters "Tasks they can do: picking," "Tasks they cannot do: working at heights," and "Limitations: using a wheelchair," that information is saved in the database.

[0183] 3. Job matching generation and notification

[0184] The server uses a matching method to match job information with user profiles and generate optimal job matches. The matching score is determined by the compatibility of the task with the user's skills and limitations. The matching results are stored in a database by the server and notified to companies and people with disabilities.

[0185] As a concrete example, the server compares the "picking" and "packing" tasks with job ID 1234 with the profile of user ID 5678 and calculates a matching score. If the score is 85, the result is saved in the database and notified to the company and the person with a disability.

[0186] 4. Real-time task notifications and assistance

[0187] The matching results are notified to the person with a disability in real time via a head-mounted display (e.g., HMD). The HMD displays the notified tasks in real time and provides instructions to assist in their completion. This streamlines task management within the logistics center and enables people with disabilities to perform tasks optimally.

[0188] As a concrete example, a person with a disability can be notified in real time, "Your next task is picking. Please take the product from the designated shelf," and can then follow the instructions to carry out the task.

[0189] Prompt Sentence Examples

[0190] Here are some examples of prompts to input to a generative AI model:

[0191] text

[0192] Consider a detailed design proposal for a system that matches the abilities of people with disabilities with job information. The system uses natural language processing to analyze job information and break it down into specific tasks. It also inputs each user's profile and matches it with job information to suggest the most suitable job.

[0193] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0194] Step 1:

[0195] Entering job information

[0196] How it works: A company recruiter enters job information in natural language on a terminal.

[0197] Input: Job summary, specific job duties, required skills and conditions.

[0198] Output: Raw job information sent to the server.

[0199] Specific operation: The company enters the job details as "Pick, pack, and move goods."

[0200] Step 2:

[0201] Job Information Analysis

[0202] How it works: The server analyzes the input job information using natural language processing (NLP) and breaks it down into multiple individual tasks.

[0203] Input: Unparsed job information.

[0204] Output: Analyzed individual tasks and associated conditions stored in a database.

[0205] Specific operation: The server breaks down the "picking and packing" job into "inventory management," "packing work," and "transportation work," and assigns conditions such as "basic arithmetic ability" and "manual dexterity" to each.

[0206] Step 3:

[0207] Entering user capabilities and limitations

[0208] How it works: A person with a disability enters their abilities and limitations in a checklist format on a terminal.

[0209] Input: Tasks that can be performed and conditions that cannot be met.

[0210] Output: Profile information of disabled people stored in a database.

[0211] Specific actions: A person with a disability enters "Tasks they can do: picking items," "Tasks they cannot do: working at heights," and "Restrictions: using a wheelchair."

[0212] Step 4:

[0213] Job Matching Generation

[0214] Operation: The server compares the stored job information with the user's capabilities and restrictions to generate the optimal job matching.

[0215] Input: Parsed job information, user profile.

[0216] Output: Matching results and matching scores.

[0217] Specific operation: The server matches the "picking" and "packing" of job ID 1234 with the profile of user ID 5678 and calculates a matching score of 85.

[0218] Step 5:

[0219] Generate and send notifications

[0220] Operation: The server stores the matching results in a database and notifies the company and the person with a disability.

[0221] Input: Job matching results.

[0222] Output: Notifications displayed on corporate and disability devices.

[0223] Specific action: The server sends a notification saying "User ID 5678 matches job ID 1234."

[0224] Step 6:

[0225] Real-time notifications and assistance

[0226] How it works: A person with a disability wears a head-mounted display (HMD) and performs tasks displayed in real time.

[0227] Input: Real-time task notifications from the server.

[0228] Output: Task instructions displayed during execution.

[0229] Specific actions: A person with a disability puts on the HMD and follows the instructions displayed, such as, "The next task is picking. Please take the product from the designated shelf."

[0230] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0231] The present invention is a system that not only analyzes job information provided by companies and breaks it down into tasks that can be performed by people with disabilities, but also combines it with an emotion engine that recognizes the emotions of users, thereby achieving more accurate job matching. Specific embodiments of the system are described below.

[0232] Overall system overview

[0233] The system consists of the following main functions:

[0234] 1. Entering and analyzing job information

[0235] 2. Input of the abilities and limitations of the person with a disability

[0236] 3. Emotion Recognition by Emotion Engine

[0237] 4. Job matching generation and notification

[0238] 1. Entering and analyzing job information

[0239] Company processing

[0240] Terminal: Provides a form for company recruiters to enter job details in natural language, including a job summary, specific job duties, and required skills and qualifications.

[0241] Server: Once job information is input, it uses natural language processing (NLP) algorithms and machine learning models to analyze it, which breaks it down into multiple specific tasks.

[0242] Server: Each decomposed task and its associated conditions (e.g., physical conditions and skill requirements) are stored in a database.

[0243] Examples:

[0244] When a company recruiter inputs "store management, purchasing management, and staff shift management," the AI ​​analyzes this and breaks it down into tasks such as "inventory management," "customer service," and "sales management." Each task is assigned a requirement such as "basic arithmetic ability" and "interpersonal skills."

[0245] 2. Input of the abilities and limitations of the person with a disability

[0246] Processing for people with disabilities

[0247] Device: Provides a checklist-style form for people with disabilities to enter their capabilities and limitations, including tasks they can perform and conditions they cannot accommodate.

[0248] Server: The information entered is stored in a database as a user profile.

[0249] Examples:

[0250] When a person with a disability enters "Tasks they can do: plating food," "Tasks they cannot do: carrying heavy objects," and "Restrictions: using a wheelchair," that information is saved in a database.

[0251] 3. Emotion Recognition by Emotion Engine

[0252] Emotion recognition processing

[0253] Device: An emotion engine is used to analyze the text and facial expressions of people with disabilities as they type, thereby determining their emotional state (e.g., tension, anxiety, relief, etc.) at the time of input.

[0254] Server: The determined emotional information is stored in a database along with the disabled person's profile.

[0255] Examples:

[0256] If a person with a disability feels "a little anxious" when filling out a form, that emotional information will also be saved.

[0257] 4. Job matching generation and notification

[0258] Matching process

[0259] Server: Checks the job details table against the user profile table to perform appropriate job matching. Specifically, it checks whether the task content and conditions match the user's available tasks and restrictions.

[0260] Server: The server also takes into account the user's emotional information and reflects it in the calculation of the matching score. For example, if a particular task is mentally demanding for the user, this will also affect the matching score.

[0261] Server: Saves the matching results, including the matching score, in a matching table and notifies companies and people with disabilities of the results. The optimal matching information for each user and job is provided.

[0262] Examples:

[0263] The server compares the tasks of "plating" and "washing dishes" with job ID 1234 with the profile of user ID 5678 and calculates a matching score. The server also takes into account the "sense of security" the user feels when "plating." If the score is 85, the result is saved in the database and notified to the company and the person with a disability.

[0264] Checking the results

[0265] Device: Company recruiters and people with disabilities can view matching results on their dashboards.

[0266] On your device: The dashboard displays your matches and their matching scores.

[0267] Through these steps, detailed job matching between companies and people with disabilities is carried out, providing more suitable employment opportunities. The system also takes into account the emotions of users, providing a matching process that reduces the mental burden.

[0268] The processing flow will be explained below.

[0269] Step 1:

[0270] User: A company's recruiter enters job information in natural language into the automated job decomposition system's input form. This information includes a job summary, specific job duties, and required skills and conditions.

[0271] Step 2:

[0272] Server: Receives input job information and passes it to a natural language processing (NLP) algorithm, which parses the job information and breaks it down into multiple individual tasks based on templates.

[0273] Step 3:

[0274] Server: The server uses machine learning models to refine the analyzed tasks and estimate the requirements for each task (e.g., specific skills or physical abilities). This determines the requirements for each task.

[0275] Step 4:

[0276] Server: Stores the decomposed tasks and their associated condition information in the task details table for later collation and matching.

[0277] Step 5:

[0278] User: A person with a disability enters information about the tasks and limitations they can perform in the form of a checklist. The checklist lists specific tasks and limitations, and the user selects which ones they can perform.

[0279] Step 6:

[0280] Device: When a person with a disability uses an input form, an emotion engine runs in the background, analyzing facial expressions and text in real time as they enter information.

[0281] Step 7:

[0282] Server: Receives the emotional data analyzed by the emotion engine, associates it with the user profile, and stores it in a database, along with the emotional state at the time of input.

[0283] Step 8:

[0284] Server: Receives task and emotion information entered by users with disabilities and stores it in a user profile table. The stored information includes tasks that can be performed, limitations, and emotion data at the time of input.

[0285] Step 9:

[0286] Server: Checks the job details table against the user profile table to perform appropriate job matching, specifically checking whether the task content and conditions match the user's available tasks and restrictions.

[0287] Step 10:

[0288] Server: The server also takes into account the user's emotional information and reflects it in the calculation of the matching score. For example, if a particular task is mentally demanding for the user, this will also affect the matching score.

[0289] Step 11:

[0290] Server: Saves the matching results, including the matching score, in a matching table and notifies companies and people with disabilities of the results. The optimal matching information for each user and job is provided.

[0291] Step 12:

[0292] Users: Company recruiters view the matching results through a dedicated dashboard, which displays a list of matching candidates and each candidate's matching score.

[0293] Step 13:

[0294] Users: People with disabilities can check their matching results through a dedicated dashboard, which displays a list of jobs that have been matched to them and their matching scores.

[0295] Through these steps, detailed job matching between companies and people with disabilities is carried out, providing more suitable employment opportunities. The system also takes into account the emotions of users, providing a matching process that reduces the mental burden.

[0296] Example 2

[0297] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0298] Conventional job matching systems only consider the user's abilities and limitations, but do not consider their emotional state, which means they are unable to match people in a way that reduces their mental burden. Furthermore, they are unable to properly analyze job information and break it down into individual tasks, which can result in poor job compatibility.

[0299] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for inputting job information provided by a company, an analysis means including artificial intelligence for analyzing the input job information and breaking it down into multiple individual tasks, a storage means for saving the analyzed individual tasks and their associated conditions in a database, an input means for a user to input their own abilities and limitations, a storage means for saving the input user ability and limitation information in the database, an analysis means for analyzing the user's emotional state using an emotion engine, a storage means for saving the saved user emotion information in the database, a matching means for collating the saved job information and user information to generate an optimal job match, and a notification means for notifying the company and the user of the matching result. This enables job matching that comprehensively takes into account the user's abilities, limitations, and emotional state, thereby achieving appropriate matching with reduced mental burden.

[0300] "Job information" is information that includes an overview of the work provided by a company, specific work content, and required skills and conditions.

[0301] An "input means" is a device or program that provides an interface for companies or users to input information into the system.

[0302] An "analysis means" is a device or program that includes artificial intelligence or natural language processing algorithms to process input information and break it down into multiple individual tasks.

[0303] The "storage means" is a device or program for storing analyzed information and input information in a database.

[0304] "User" means a person with a disability or their representative who uses the system to input their capabilities and limitations.

[0305] An "emotion engine" is a device or program that analyzes a user's input and facial expressions to determine their emotional state.

[0306] The "matching means" is a device or program for matching the stored job information with the user information and emotion information to generate optimal job matching.

[0307] The "notification means" is a device or program for notifying companies and users of the generated matching results.

[0308] The "matching score" is a numerical representation of the degree of compatibility between job information and user information.

[0309] The present invention is a system that not only analyzes job information provided by companies and breaks it down into tasks that can be performed by people with disabilities, but also combines it with an emotion engine that recognizes the emotions of users, thereby achieving more accurate job matching. Specific embodiments of the system are described below.

[0310] Overall system overview

[0311] The system consists of the following main functions:

[0312] 1. Entering and analyzing job information

[0313] 2. Input of the abilities and limitations of the person with a disability

[0314] 3. Emotion Recognition by Emotion Engine

[0315] 4. Job matching generation and notification

[0316] Entering and parsing job information

[0317] Terminal: A company's recruiter fills in the job details using an input form, which includes a job summary, specific job duties, and required skills and qualifications.

[0318] Examples:

[0319] A company's recruiter would enter "store management, purchasing management, staff shift management."

[0320] Server: Receives the input job information and analyzes it using a natural language processing (NLP) algorithm. Through analysis, the job information is broken down into multiple specific tasks.

[0321] Examples:

[0322] The server receives the "store management, purchasing management, staff shift management" and breaks it down into tasks such as "inventory management," "customer support," and "sales management."

[0323] Server: The decomposed tasks and their associated conditions (e.g., physical conditions and skill requirements) are stored in a database.

[0324] Input of abilities and limitations of people with disabilities

[0325] Device: People with disabilities enter the tasks they can perform and the conditions they cannot deal with into a checklist-style input form.

[0326] Examples:

[0327] A person with a disability would enter "Tasks they can do: plating," "Tasks they cannot do: carrying heavy objects," and "Limitations: using a wheelchair."

[0328] Server: Saves the entered information as a user profile in a database.

[0329] Emotion recognition by emotion engine

[0330] Terminal: Using an emotion engine, the text and facial expressions entered by the person with a disability are analyzed to determine their emotional state at the time of input (e.g., tension, anxiety, relief, etc.).

[0331] Examples:

[0332] Detects the emotional state of "slight anxiety" felt by people with disabilities when entering information into an input form.

[0333] Server: Stores the determined emotion information in a database along with the user profile.

[0334] Job matching generation and notification

[0335] Server: Matches the job details table with the user profile table to perform appropriate job matching. Checks whether the task content and conditions match the user's available tasks and restrictions.

[0336] Examples:

[0337] The server compares the tasks of "plating" and "washing dishes" with job ID 1234 with the profile of user ID 5678 and calculates a matching score. At this time, it also takes into account the "sense of security" the user feels when "plating."

[0338] Server: Stores the matching results, including the matching score, in a matching table and notifies the companies and people with disabilities of the results.

[0339] Device: Company recruiters and people with disabilities can check the matching results on their respective dashboards.

[0340] Prompt Sentence Examples

[0341] Here are some examples of prompts to input to the generative AI model:

[0342] Analyze job information entered by company recruiters and break it down into appropriate tasks. Then, perform job matching and generate matching results taking into account the abilities and limitations of the disabled persons entered. Optimize the results by also taking into account the emotional information of the disabled persons.

[0343] Through these steps, the system performs detailed job matching between companies and people with disabilities, providing more suitable employment opportunities. It also takes into account the user's feelings, providing a matching process that reduces the mental burden.

[0344] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0345] Step 1: Enter job information

[0346] Terminal: The company's recruiter enters job details into the input form, including a job summary, specific job duties, and required skills and conditions.

[0347] Input: Enter job details (e.g., "Store management, stock management, staff shift management").

[0348] Specific operation: A recruiter enters job information into a form on the terminal, and the information is sent to the server.

[0349] Step 2: Job information analysis and task decomposition

[0350] Server: The server receives the job information, analyzes it using a natural language processing (NLP) algorithm, and breaks down the analysis results into multiple specific tasks.

[0351] Input: Received job information.

[0352] Data processing / calculation: Job information is analyzed using natural language processing and broken down into individual tasks.

[0353] Output: Decomposed task information (e.g., "Inventory management," "Customer support," "Sales management").

[0354] Specific operation: The server breaks down "store management, purchasing management, staff shift management" into "inventory management," "customer support," and "sales management."

[0355] Step 3: Save task information

[0356] Server: Stores the decomposed task information and its associated conditions (e.g., physical conditions and skill requirements) in a database.

[0357] Input: Decomposed task information.

[0358] Data processing / calculation: Task information and conditions are associated and saved in the database.

[0359] Output: The saved database entries.

[0360] Specific operation: Assign conditions such as "basic arithmetic ability" and "interpersonal skills" to "inventory management" and store this information in a database.

[0361] Step 4: Enter the abilities and limitations of the person with a disability

[0362] Device: People with disabilities enter the tasks they can perform and the conditions they cannot deal with into a checklist-style input form.

[0363] Input: Information about the abilities and limitations of the person with a disability (e.g., "Tasks that can be done: plating food," "Tasks that cannot be done: lifting heavy objects," "Limitations: using a wheelchair").

[0364] Specific operation: A person with a disability enters their abilities and limitations into a form on the device, and that information is sent to the server.

[0365] Step 5: Save your user profile

[0366] Server: The entered information about the abilities and limitations of the disabled person is saved in a database as a user profile.

[0367] Input: Disability ability and limitation information.

[0368] Data processing / calculation: Convert the input information into a profile format and save it in the database.

[0369] Output: The saved user profile.

[0370] Specific actions: Information on "serving food," "carrying heavy objects," and "using a wheelchair" is stored in a database.

[0371] Step 6: Emotion Recognition with the Emotion Engine

[0372] Device: An emotion engine is used to analyze the text and facial expressions of people with disabilities as they type, thereby determining their emotional state (e.g., tension, anxiety, relief, etc.) at the time of input.

[0373] Input: Input and facial expression data from the person with a disability.

[0374] Data processing / calculation: The emotion engine analyzes input content and facial expressions to determine the emotional state.

[0375] Output: Determined emotion information (e.g., "anxiety").

[0376] Specific operation: The system detects "anxiety" from the facial expressions and writing of people with disabilities.

[0377] Step 7: Storing Emotional Information

[0378] Server: Stores the determined emotion information in a database along with the user profile.

[0379] Input: Determined emotion information.

[0380] Data processing / calculation: Emotional information is added to the user profile and stored in the database.

[0381] Output: The updated user profile.

[0382] Specific behavior: Save the emotional information "anxiety" along with the profile data.

[0383] Step 8: Match job details with user profile

[0384] Server: Matches the job details table with the user profile table to perform appropriate job matching. Checks whether the task content and conditions match the user's available tasks and restrictions.

[0385] Input: Job details and user profile information.

[0386] Data processing / calculation: Compare job details with user profile and calculate compatibility.

[0387] Output: Matching results and matching score (e.g., matching score of 85 for the tasks "plating" and "washing dishes").

[0388] Specific operation: The server matches the tasks "plating" and "washing dishes" of job ID 1234 with the profile of user ID 5678 and calculates the matching score.

[0389] Step 9: Notification of Matching Results

[0390] Server: Stores the matching results, including the matching score, in a matching table and notifies the companies and people with disabilities of the results.

[0391] Input: Matching results and matching scores.

[0392] Data processing / calculation: The matching results and matching scores are stored as a set in the matching table, and a notification message is generated.

[0393] Output: Notification message (e.g., "Matching result: Job ID 1234, score 85").

[0394] Specific operation: The matching score of 85 is saved in the database and notified to the company and the person with a disability.

[0395] Step 10: Check the results

[0396] Device: Company recruiters and people with disabilities can view matching results on their dashboards.

[0397] Input: Your dashboard login details.

[0398] Output: A screen showing the matching results and matching scores.

[0399] What it does: Corporate recruiters and people with disabilities can view matched candidates and their matching scores on a dashboard.

[0400] Through these processing steps, the system performs detailed job matching between companies and people with disabilities, providing appropriate employment opportunities. It also takes into account the user's feelings, making it possible to provide a matching process that reduces the mental burden.

[0401] (Application example 2)

[0402] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0403] It is necessary to improve the work efficiency of people with disabilities working in factories while reducing their mental burden. In particular, there is a need to achieve more accurate job matching by breaking down job information into tasks that are appropriate for the abilities of people with disabilities and by taking into account their emotional state at the time. It is also important to provide an environment where people with disabilities can work in real time in an emotionally appropriate state.

[0404] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0405] In this invention, the server includes: an input means for inputting job information provided by a company; an analysis means including artificial intelligence for analyzing the input job information and breaking it down into multiple individual tasks; a storage means for saving the analyzed individual tasks and their associated conditions in a database; an input means for a user to input their own abilities and limitations; a storage means for saving the input user's ability and limitation information in the database; a matching means for collating the saved job information with user information to generate an optimal job match; a notification means for notifying the company and the user of the matching results; an emotion engine that recognizes the user's emotional state; a storage means for saving the emotion information recognized by the emotion engine in a profile; and a matching means for calculating a matching score taking the user's emotion information into consideration. This allows individuals with disabilities to be assigned tasks that are suited to their abilities and to work with less mental strain.

[0406] An "input means" is a device or method for receiving data. It typically includes a keyboard, mouse, touch screen, voice input device, etc.

[0407] "Analysis means" refers to a device or method for breaking down input data and understanding its meaning and structure. This includes artificial intelligence and natural language processing algorithms.

[0408] "Artificial intelligence" is a technology that allows computer systems to imitate human intellectual behavior and make judgments and learn.

[0409] "Storage" means a device or method for long-term storage of data. This includes databases and cloud storage.

[0410] A "database" is a structured collection of data that is systematically organized, stored, and can be efficiently searched and updated.

[0411] A "matching means" is a device or method for comparing different data to evaluate the degree of agreement or compatibility.

[0412] "Notification medium" means a device or method for communicating information to a specific person or system, including email, SMS, in-app notifications, etc.

[0413] An "emotion engine" is a device or method for analyzing and identifying a user's emotional state. It includes technologies such as facial expression recognition and voice analysis.

[0414] A "profile" is a collection of information about a particular user, including their capabilities, limitations, emotional state, etc.

[0415] A "matching score" is a numerical representation of the degree of suitability or agreement of the matching result. For example, it may include an evaluation score out of 100 points.

[0416] This invention is a system that improves the work efficiency and reduces the mental burden of disabled workers in factories. The system includes the following main components and functions:

[0417] 1. Entering and analyzing job information

[0418] Company processing

[0419] The server provides input means for company recruiters to enter job details. This input means can include a text input form or a voice input device. The entered job information is received by the server and broken down into multiple individual tasks using a natural language processing (NLP) algorithm. The analyzed individual tasks are then stored in a database.

[0420] 2. Input of the abilities and limitations of the person with a disability

[0421] Processing for people with disabilities

[0422] The device provides an input method for people with disabilities to enter their capabilities and limitations. This input method can be a checklist-style form or a touchscreen. The information entered is stored in a database as a user profile.

[0423] 3. Emotion Recognition by Emotion Engine

[0424] Emotion recognition processing

[0425] The device uses an emotion engine to analyze the text and facial expressions entered by users with disabilities. This emotion engine uses hardware such as a facial recognition camera and a voice analyzer, as well as software such as EmotionRecognizer. The emotional information that is identified is stored in a database along with the user profile.

[0426] 4. Job matching generation and notification

[0427] Matching process

[0428] The server compares the job details table with the user profile table to perform appropriate job matching. It checks whether the task content and conditions match the user's available tasks and constraints. It also calculates a matching score taking into account the user's emotional information. The calculation results are saved in the matching table and notified to the company and the person with a disability.

[0429] Specific examples

[0430] If a disabled factory worker inputs "I'll do my best today," the emotion recognition engine will detect positive emotions such as "relief." When job information such as "store management, purchasing management, and staff shift management" is given, this information is broken down into tasks such as "inventory management," "customer service," and "sales management." The broken down tasks are then compared with the user profile to match the most suitable tasks.

[0431] Prompt Sentence Examples

[0432] Job information: Store management, purchasing management, staff shift management

[0433] Emotion input: I'll do my best today too

[0434] User profile: Possible tasks: Inventory management, sales management; Impossible tasks: Customer support

[0435] This system allows people with disabilities to be assigned tasks that suit their abilities, allowing them to work with less mental strain.

[0436] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0437] Step 1:

[0438] A company's recruiter uses a terminal to input job information. Input methods include text input forms and voice input devices. Job details such as "store management, purchasing management, and staff shift management" are entered. The server receives the input job information and temporarily stores it in a database.

[0439] Input: Job information (text or audio format)

[0440] Output: Saved job information

[0441] Step 2:

[0442] The server analyzes the input job information using a natural language processing (NLP) algorithm and breaks it down into multiple individual tasks. For example, job information such as "store management, purchasing management, and staff shift management" is broken down into specific tasks such as "inventory management," "customer service," and "sales management." Each broken down task is assigned related conditions (such as required skills and physical conditions) and stored in a database.

[0443] Input: Job information

[0444] Output: Analyzed individual tasks and associated conditions

[0445] Step 3:

[0446] The terminal provides an input means for people with disabilities to enter their abilities and limitations. To do this, people with disabilities use a checklist-style form or a touch screen to enter information such as "possible task: serving food," "impossible task: carrying heavy objects," and "limitations: using a wheelchair." The entered ability and limitation information is received by the server and stored in a database as a user profile.

[0447] Input: Disability capabilities and limitations information

[0448] Output: Saved user profile

[0449] Step 4:

[0450] The device uses an emotion engine to analyze the text and facial expressions entered by the person with a disability. For example, if a person with a disability enters "I'll do my best today," the emotion engine analyzes their facial expression and tone of voice to identify positive emotions such as "relief." The recognized emotion information is then added to a profile by the server.

[0451] Input: Text and facial expression data of a person with a disability

[0452] Output: Parsed emotion information

[0453] Step 5:

[0454] The server compares the stored job information with the user profile to generate optimal job matching. Task content and conditions are matched based on the user's available tasks and constraints. Furthermore, the server also considers the user's emotional information and calculates a matching score to minimize mental strain. For example, if a particular task is mentally stressful for the user, the score for that task will be reduced.

[0455] Input: Job information, user profile, emotion information

[0456] Output: Matching score and matching result

[0457] Step 6:

[0458] The server notifies the company and the person with a disability of the matching results via email, SMS, in-app notifications, etc. The company's recruiter and the person with a disability can check the matching results on their dashboard and receive instructions for performing the appropriate tasks.

[0459] Input: Matching results

[0460] Output: Notified matching results

[0461] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0462] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0463] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0464] [Second embodiment]

[0465] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0466] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0467] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0468] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0469] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0470] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0471] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0472] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0473] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0474] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0475] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0476] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0477] The present invention is a system that realizes optimal job matching by analyzing job information provided by companies and breaking it down into tasks that can be performed by people with disabilities. Specific embodiments of the system are described below.

[0478] Overall system overview

[0479] The system consists of the following main functions:

[0480] 1. Entering and analyzing job information

[0481] 2. Input of the abilities and limitations of the person with a disability

[0482] 3. Job matching generation and notification

[0483] 1. Entering and analyzing job information

[0484] Company processing

[0485] Terminal: Provides a form for company recruiters to enter job details in natural language, including a job summary, specific job duties, and required skills and qualifications.

[0486] Server: Once job information is input, it uses natural language processing (NLP) algorithms and machine learning models to analyze it, which breaks it down into multiple specific tasks.

[0487] Server: Each decomposed task and its associated conditions (e.g., physical conditions and skill requirements) are stored in a database.

[0488] Examples:

[0489] When a company recruiter inputs "store management, purchasing management, and staff shift management," the AI ​​analyzes this and breaks it down into tasks such as "inventory management," "customer service," and "sales management." Each task is assigned a requirement such as "basic arithmetic ability" and "interpersonal skills."

[0490] 2. Input of the abilities and limitations of the person with a disability

[0491] Processing for people with disabilities

[0492] Device: Provides a checklist-style form for people with disabilities to enter their capabilities and limitations, including tasks they can perform and conditions they cannot accommodate.

[0493] Server: The information entered is stored in a database as a user profile.

[0494] Examples:

[0495] When a person with a disability enters "Tasks they can do: plating food," "Tasks they cannot do: carrying heavy objects," and "Restrictions: using a wheelchair," that information is saved in a database.

[0496] 3. Job matching generation and notification

[0497] Matching process

[0498] Server: Matches the job details table with the user profile table and generates matching candidates based on matching tasks and conditions.

[0499] Server: Calculates the matching score and generates the best job matching based on it. The matching score is determined by the compatibility of the task and the user's skills and constraints.

[0500] Server: Stores the matching results in a database and notifies companies and people with disabilities of the results.

[0501] Examples:

[0502] The server compares the tasks of "plating" and "washing dishes" with job ID 1234 with the profile of user ID 5678 and calculates a matching score. If the score is 85, the result is saved in the database and notified to the company and the person with a disability.

[0503] Checking the results

[0504] Device: Company recruiters and people with disabilities can view matching results on their dashboards.

[0505] On your device: The dashboard displays your matches and their matching scores.

[0506] In this way, this system analyzes companies' job information in detail and matches jobs that suit the abilities and limitations of people with disabilities, aiming to increase employment opportunities for people with disabilities and reduce turnover rates.

[0507] The processing flow will be explained below.

[0508] Step 1:

[0509] User: A company's recruiter enters job information in natural language into the automated job decomposition system's input form. This information includes a job summary, specific job duties, and required skills and conditions.

[0510] Step 2:

[0511] Server: Receives input job information and passes it to a natural language processing (NLP) algorithm, which parses the job information and breaks it down into multiple individual tasks based on templates.

[0512] Step 3:

[0513] Server: The server uses machine learning models to refine the analyzed tasks and estimate the requirements for each task (e.g., specific skills or physical abilities). This determines the requirements for each task.

[0514] Step 4:

[0515] Server: Stores the decomposed tasks and their associated condition information in the task details table for later collation and matching.

[0516] Step 5:

[0517] User: A person with a disability enters information about the tasks and limitations they can perform in the form of a checklist. The checklist lists specific tasks and limitations, and the user selects which ones they can perform.

[0518] Step 6:

[0519] Server: Receives the information entered by the person with a disability and stores it in a user profile table, including the tasks they can perform and their limitations.

[0520] Step 7:

[0521] Server: Checks the stored job details table against the user profile table to perform appropriate job matching, specifically checking whether the task content and conditions match the user's available tasks and restrictions.

[0522] Step 8:

[0523] Server: Calculates a matching score based on the compatibility between the job and the user. The matching score is determined by the degree to which each task matches the user's skills and constraints.

[0524] Step 9:

[0525] Server: Saves the matching results, including the matching score, in a matching table and notifies companies and people with disabilities of the results. The optimal matching information for each user and job is provided.

[0526] Step 10:

[0527] Users: Company recruiters view the matching results through a dedicated dashboard, which displays a list of matching candidates and each candidate's matching score.

[0528] Step 11:

[0529] Users: People with disabilities can check their matching results through a dedicated dashboard, which displays a list of jobs that have been matched to them and their matching scores.

[0530] Through these steps, detailed job matching will be carried out between companies and people with disabilities, providing more appropriate employment opportunities.

[0531] Example 1

[0532] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0533] In recent years, companies have been providing a wide variety of job information, but it is difficult for people with disabilities to find tasks that they can perform appropriately. It is also difficult for people with disabilities themselves to find jobs that suit their abilities and limitations, which reduces employment opportunities and contributes to high turnover rates. Current systems often lack sufficient analysis of job information and do not properly generate or match task lists suitable for people with disabilities. Therefore, there is a need for an effective system that allows people with disabilities to find jobs that suit them and companies to hire the right personnel.

[0534] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0535] In this invention, the server includes an input means for inputting job information provided by a company, an analysis means including artificial intelligence for analyzing the input job information and breaking it down into multiple individual tasks, a storage means for saving the analyzed individual tasks and their associated conditions in a database, an input means for a user to input their own abilities and limitations, a storage means for saving the input user ability and limitation information in the database, a comparison means for comparing the saved job information with user information to generate optimal job matching, a notification means for notifying the company and user of the comparison results, and a display means for displaying the comparison results on a dashboard. This enables detailed analysis of company job information and job matching that is appropriate for the abilities and limitations of people with disabilities.

[0536] "Company" refers to an organization that provides job information and conducts recruitment activities.

[0537] "Job information" refers to information provided by companies, such as job content, required skills, conditions, etc.

[0538] "Input means" refers to an interface through which a user inputs text and options.

[0539] The "analysis means" is a system that uses artificial intelligence to analyze input job information and break it down into multiple individual tasks.

[0540] "Artificial intelligence" is a technology that uses natural language processing and machine learning models to analyze and classify data.

[0541] "Storage means" refers to a system that stores analyzed data and input information in a database.

[0542] "User" refers to a person with a disability who uses the system.

[0543] "Ability" refers to the tasks a user can perform and the skills they possess.

[0544] "Limitations" refers to constraints such as tasks that a user cannot perform or physical conditions that the user has.

[0545] The "matching means" is a system that generates optimal job matching based on the stored job information and user information.

[0546] "Notification means" is a system for notifying companies and users of the matching results.

[0547] A "display means" is a system that visually displays information to a user through an interface such as a dashboard.

[0548] The present invention is a system that realizes optimal job matching by analyzing job information provided by companies and breaking it down into tasks that can be performed by people with disabilities. Specific embodiments of the system are described below.

[0549] System Overview

[0550] The system consists of the following main hardware and software components:

[0551] Devices: Computers, smartphones, or other devices used by company recruiters and people with disabilities to enter information.

[0552] Server: A computer system that analyzes input data and stores, collates, and notifies users. Specific examples include Apache and Nginx servers.

[0553] Database: A database system for storing analyzed job information and user profiles. Specific examples include MySQL and PostgreSQL.

[0554] Artificial intelligence models: Natural language processing (NLP) algorithms and machine learning models used to parse job information and break it down into tasks. Specific examples include Python's NLTK, SpaCy, TensorFlow, and Scikit-learn.

[0555] Specific processing flow

[0556] 1. Entering and analyzing job information

[0557] Terminal: A company's recruiter enters job details into an input form, which includes a job summary, specific job duties, and required skills and conditions.

[0558] Example: A recruiter enters "store management, purchasing management, staff shift management."

[0559] Server: Once job information is entered, it is analyzed using natural language processing (NLP) algorithms and machine learning models. As a result of the analysis, the job information is broken down into multiple specific tasks.

[0560] Example: The server breaks down job information into tasks such as "inventory management," "customer support," and "sales management."

[0561] Server: Each decomposed task and its associated conditions (e.g., physical conditions and skill requirements) are stored in a database.

[0562] 2. Input of the abilities and limitations of the person with a disability

[0563] Device: People with disabilities enter their capabilities and limitations using a checklist-style form, which lists the tasks they can perform and the conditions they cannot accommodate.

[0564] Example: A person with a disability enters "Tasks I can do: Placing food on the table," "Tasks I cannot do: Carrying heavy objects," and "Restrictions: Using a wheelchair."

[0565] Server: The entered information is stored in a database as a user profile.

[0566] 3. Job matching generation and notification

[0567] Server: Compares the job details table with the user profile table and generates matching candidates based on compatible tasks and conditions. Specifically, it uses natural language processing and machine learning models to calculate the compatibility between tasks and user profiles.

[0568] Example: The server matches the "plating" task with the user's profile and calculates a matching score.

[0569] Server: Generates optimal job matches based on the matching scores, stores the results in a database, and notifies companies and people with disabilities of the results.

[0570] 4. Check the results

[0571] Device: Corporate recruiters and people with disabilities can check their matching results on their own dashboard.

[0572] Example: Companies and people with disabilities evaluate the matching results confirmed through the dashboard and take the following actions:

[0573] Prompt Sentence Examples

[0574] Analyze job information entered by companies, break it down into specific tasks, and compare it with the abilities and limitations entered by individuals with disabilities to generate an appropriate job matching score.

[0575] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0576] Step 1:

[0577] The terminal provides an input form for company recruiters to enter job details. The recruiter inputs the job summary, specific work content, required skills and conditions in natural language. This input sends the job information to the server. Input data includes "store management, purchasing management, staff shift management," etc.

[0578] Step 2:

[0579] The server stores the received job information in a temporary database, which is used for later analysis. The stored data is the entire job information entered.

[0580] Step 3:

[0581] The server begins to analyze the stored job information. Using natural language processing (NLP) algorithms (such as Python's NLTK or SpaCy) and machine learning models (such as TensorFlow or Scikit-learn), it analyzes the job information and breaks it down into multiple specific tasks. The input data is the entire job information, and the output data is the broken down task list and corresponding conditions. For example, the job information is broken down into the tasks "inventory management," "customer support," and "sales management."

[0582] Step 4:

[0583] The server stores each decomposed task and its associated conditions in a database. The stored data includes detailed information about each task (e.g., "basic arithmetic ability" for "inventory management" and "interpersonal skills" for "customer service").

[0584] Step 5:

[0585] The device provides a checklist-style input form for people with disabilities to enter their abilities and limitations. People with disabilities enter the tasks they can do and the conditions they cannot handle. This input creates a user profile, which is sent to the server. Input data includes such things as "Tasks they can do: plating food," "Tasks they cannot do: carrying heavy objects," and "Limitations: using a wheelchair."

[0586] Step 6:

[0587] The server stores the data received from the disabled person in a temporary database, which is later used for matching purposes. The stored data is the entire entered user profile.

[0588] Step 7:

[0589] The server compares the saved job information with the user profile and generates matching candidates based on compatible tasks and conditions. This uses natural language processing and machine learning models, with the input data being the job details table and user profile table, and the output data being the matching candidates. The server calculates the compatibility between the task and the user's skills and restrictions, and calculates a matching score. As a specific example, the task "plating" is compared with the user's profile, and the matching score is calculated as 75 points.

[0590] Step 8:

[0591] The server stores the matching results in a database and notifies the company and the person with a disability of the results. The stored data is the matching score and the corresponding task list, and the notification includes the job ID, user ID, and compatibility score.

[0592] Step 9:

[0593] The device provides an interface for corporate recruiters and people with disabilities to check matching results on their own dashboards. The data displayed is the matched candidates and their matching scores. For example, the dashboard might show that "User ID 5678 matches Job ID 1234 with a matching score of 75."

[0594] (Application example 1)

[0595] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0596] Previously, there were systems that analyzed job information provided by companies and matched them with tasks suitable for people with disabilities, but these systems did not support real-time task notifications or execution support, making it difficult for people with disabilities to continuously perform appropriate tasks at work sites such as logistics centers.In addition, people with disabilities could not easily recognize or understand the optimal tasks according to their own situation, making it difficult to increase employment opportunities and achieve efficient work.

[0597] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0598] In this invention, the server includes: an input means for inputting job information provided by a company; an analysis means including artificial intelligence for analyzing the input job information and breaking it down into multiple individual tasks; a storage means for saving the analyzed individual tasks and their associated conditions in a database; an input means for a user to input their own abilities and limitations; a storage means for saving the input user ability and limitation information in the database; a matching means for collating the saved job information and user information to generate optimal job matching; a notification means for notifying the company and the user of the matching results; and a head-mounted display including a display device for displaying the notified tasks in real time and supporting their completion. This enables people with disabilities at logistics centers to recognize and appropriately complete the tasks that are optimal for them in real time.

[0599] An "enterprise" is an organization that conducts business, such as a company or corporation.

[0600] "Job information" refers to information provided by a company, such as the business content, job details, required skills and conditions, etc.

[0601] "Input means" means a device or software for inputting information into a system.

[0602] "Analysis means" refers to a device or software that breaks down input information and extracts meaning.

[0603] "Artificial intelligence" is a technology that uses machine learning and natural language processing to analyze data and solve problems.

[0604] "Storage means" refers to a device or software for storing data for a certain period of time.

[0605] A "database" is a system for efficiently storing, managing, and searching data.

[0606] "User" refers to any person, including a person with a disability, who uses the system and receives tasks.

[0607] "Ability" refers to the skills and tasks that a user can perform.

[0608] "Limitations" refer to skills or tasks that a user cannot perform.

[0609] The "matching means" refers to a device or software that compares the stored job information with the user information and derives the optimal match.

[0610] "Notification means" means a device or software for notifying users of match results or other information.

[0611] A "head-mounted display" is a device worn on the head to display information.

[0612] "Real-time" refers to processing and information exchange occurring instantly with little or no delay.

[0613] Overall system overview

[0614] This invention is a system for efficiently matching tasks for people with disabilities in logistics centers. The system inputs and analyzes job information, inputs the abilities and limitations of people with disabilities, generates and notifies job matching, and provides real-time task notification and execution support.

[0615] 1. Entering and analyzing job information

[0616] The company's terminal has an input means for entering job information. The entered job information is analyzed by the server. Natural language processing (NLP) and machine learning models are used for the analysis. This breaks down the job information into multiple individual tasks. The analyzed tasks and their associated conditions are stored in a database by the server.

[0617] For example, if a company recruiter inputs "stock organization, packing, and product movement," the AI ​​will break this down into "inventory management," "packing work," and "transportation work." Each task will be assigned a condition such as "basic arithmetic ability" or "manual dexterity."

[0618] 2. Input of the abilities and limitations of the person with a disability

[0619] The device on the disabled person's side has a checklist-style input means for entering their abilities and limitations. The input information is saved in a database as a user profile, which clarifies the tasks that the disabled person can perform and their limitations.

[0620] For example, if a person with a disability enters "Tasks they can do: picking," "Tasks they cannot do: working at heights," and "Limitations: using a wheelchair," that information is saved in the database.

[0621] 3. Job matching generation and notification

[0622] The server uses a matching method to match job information with user profiles and generate optimal job matches. The matching score is determined by the compatibility of the task with the user's skills and limitations. The matching results are stored in a database by the server and notified to companies and people with disabilities.

[0623] As a concrete example, the server compares the "picking" and "packing" tasks with job ID 1234 with the profile of user ID 5678 and calculates a matching score. If the score is 85, the result is saved in the database and notified to the company and the person with a disability.

[0624] 4. Real-time task notifications and assistance

[0625] The matching results are notified to the person with a disability in real time via a head-mounted display (e.g., HMD). The HMD displays the notified tasks in real time and provides instructions to assist in their completion. This streamlines task management within the logistics center and enables people with disabilities to perform tasks optimally.

[0626] As a concrete example, a person with a disability can be notified in real time, "Your next task is picking. Please take the product from the designated shelf," and can then follow the instructions to carry out the task.

[0627] Prompt Sentence Examples

[0628] Here are some examples of prompts to input to a generative AI model:

[0629] text

[0630] Consider a detailed design proposal for a system that matches the abilities of people with disabilities with job information. The system uses natural language processing to analyze job information and break it down into specific tasks. It also inputs each user's profile and matches it with job information to suggest the most suitable job.

[0631] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0632] Step 1:

[0633] Entering job information

[0634] How it works: A company recruiter enters job information in natural language on a terminal.

[0635] Input: Job summary, specific job duties, required skills and conditions.

[0636] Output: Raw job information sent to the server.

[0637] Specific operation: The company enters the job details as "Pick, pack, and move goods."

[0638] Step 2:

[0639] Job Information Analysis

[0640] How it works: The server analyzes the input job information using natural language processing (NLP) and breaks it down into multiple individual tasks.

[0641] Input: Unparsed job information.

[0642] Output: Analyzed individual tasks and associated conditions stored in a database.

[0643] Specific operation: The server breaks down the "picking and packing" job into "inventory management," "packing work," and "transportation work," and assigns conditions such as "basic arithmetic ability" and "manual dexterity" to each.

[0644] Step 3:

[0645] Entering user capabilities and limitations

[0646] How it works: A person with a disability enters their abilities and limitations in a checklist format on a terminal.

[0647] Input: Tasks that can be performed and conditions that cannot be met.

[0648] Output: Profile information of disabled people stored in a database.

[0649] Specific actions: A person with a disability enters "Tasks they can do: picking items," "Tasks they cannot do: working at heights," and "Restrictions: using a wheelchair."

[0650] Step 4:

[0651] Job Matching Generation

[0652] Operation: The server compares the stored job information with the user's capabilities and restrictions to generate the optimal job matching.

[0653] Input: Parsed job information, user profile.

[0654] Output: Matching results and matching scores.

[0655] Specific operation: The server matches the "picking" and "packing" of job ID 1234 with the profile of user ID 5678 and calculates a matching score of 85.

[0656] Step 5:

[0657] Generate and send notifications

[0658] Operation: The server stores the matching results in a database and notifies the company and the person with a disability.

[0659] Input: Job matching results.

[0660] Output: Notifications displayed on corporate and disability devices.

[0661] Specific action: The server sends a notification saying "User ID 5678 matches job ID 1234."

[0662] Step 6:

[0663] Real-time notifications and assistance

[0664] How it works: A person with a disability wears a head-mounted display (HMD) and performs tasks displayed in real time.

[0665] Input: Real-time task notifications from the server.

[0666] Output: Task instructions displayed during execution.

[0667] Specific actions: A person with a disability puts on the HMD and follows the instructions displayed, such as, "The next task is picking. Please take the product from the designated shelf."

[0668] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0669] The present invention is a system that not only analyzes job information provided by companies and breaks it down into tasks that can be performed by people with disabilities, but also combines it with an emotion engine that recognizes the emotions of users, thereby achieving more accurate job matching. Specific embodiments of the system are described below.

[0670] Overall system overview

[0671] The system consists of the following main functions:

[0672] 1. Entering and analyzing job information

[0673] 2. Input of the abilities and limitations of the person with a disability

[0674] 3. Emotion Recognition by Emotion Engine

[0675] 4. Job matching generation and notification

[0676] 1. Entering and analyzing job information

[0677] Company processing

[0678] Terminal: Provides a form for company recruiters to enter job details in natural language, including a job summary, specific job duties, and required skills and qualifications.

[0679] Server: Once job information is input, it uses natural language processing (NLP) algorithms and machine learning models to analyze it, which breaks it down into multiple specific tasks.

[0680] Server: Each decomposed task and its associated conditions (e.g., physical conditions and skill requirements) are stored in a database.

[0681] Examples:

[0682] When a company recruiter inputs "store management, purchasing management, and staff shift management," the AI ​​analyzes this and breaks it down into tasks such as "inventory management," "customer service," and "sales management." Each task is assigned a requirement such as "basic arithmetic ability" and "interpersonal skills."

[0683] 2. Input of the abilities and limitations of the person with a disability

[0684] Processing for people with disabilities

[0685] Device: Provides a checklist-style form for people with disabilities to enter their capabilities and limitations, including tasks they can perform and conditions they cannot accommodate.

[0686] Server: The information entered is stored in a database as a user profile.

[0687] Examples:

[0688] When a person with a disability enters "Tasks they can do: plating food," "Tasks they cannot do: carrying heavy objects," and "Restrictions: using a wheelchair," that information is saved in a database.

[0689] 3. Emotion Recognition by Emotion Engine

[0690] Emotion recognition processing

[0691] Device: An emotion engine is used to analyze the text and facial expressions of people with disabilities as they type, thereby determining their emotional state (e.g., tension, anxiety, relief, etc.) at the time of input.

[0692] Server: The determined emotional information is stored in a database along with the disabled person's profile.

[0693] Examples:

[0694] If a person with a disability feels "a little anxious" when filling out a form, that emotional information will also be saved.

[0695] 4. Job matching generation and notification

[0696] Matching process

[0697] Server: Checks the job details table against the user profile table to perform appropriate job matching. Specifically, it checks whether the task content and conditions match the user's available tasks and restrictions.

[0698] Server: The server also takes into account the user's emotional information and reflects it in the calculation of the matching score. For example, if a particular task is mentally demanding for the user, this will also affect the matching score.

[0699] Server: Saves the matching results, including the matching score, in a matching table and notifies companies and people with disabilities of the results. The optimal matching information for each user and job is provided.

[0700] Examples:

[0701] The server compares the tasks of "plating" and "washing dishes" with job ID 1234 with the profile of user ID 5678 and calculates a matching score. The server also takes into account the "sense of security" the user feels when "plating." If the score is 85, the result is saved in the database and notified to the company and the person with a disability.

[0702] Checking the results

[0703] Device: Company recruiters and people with disabilities can view matching results on their dashboards.

[0704] On your device: The dashboard displays your matches and their matching scores.

[0705] Through these steps, detailed job matching between companies and people with disabilities is carried out, providing more suitable employment opportunities. The system also takes into account the emotions of users, providing a matching process that reduces the mental burden.

[0706] The processing flow will be explained below.

[0707] Step 1:

[0708] User: A company's recruiter enters job information in natural language into the automated job decomposition system's input form. This information includes a job summary, specific job duties, and required skills and conditions.

[0709] Step 2:

[0710] Server: Receives input job information and passes it to a natural language processing (NLP) algorithm, which parses the job information and breaks it down into multiple individual tasks based on templates.

[0711] Step 3:

[0712] Server: The server uses machine learning models to refine the analyzed tasks and estimate the requirements for each task (e.g., specific skills or physical abilities). This determines the requirements for each task.

[0713] Step 4:

[0714] Server: Stores the decomposed tasks and their associated condition information in the task details table for later collation and matching.

[0715] Step 5:

[0716] User: A person with a disability enters information about the tasks and limitations they can perform in the form of a checklist. The checklist lists specific tasks and limitations, and the user selects which ones they can perform.

[0717] Step 6:

[0718] Device: When a person with a disability uses an input form, an emotion engine runs in the background, analyzing facial expressions and text in real time as they enter information.

[0719] Step 7:

[0720] Server: Receives the emotional data analyzed by the emotion engine, associates it with the user profile, and stores it in a database, along with the emotional state at the time of input.

[0721] Step 8:

[0722] Server: Receives task and emotion information entered by users with disabilities and stores it in a user profile table. The stored information includes tasks that can be performed, limitations, and emotion data at the time of input.

[0723] Step 9:

[0724] Server: Checks the job details table against the user profile table to perform appropriate job matching, specifically checking whether the task content and conditions match the user's available tasks and restrictions.

[0725] Step 10:

[0726] Server: The server also takes into account the user's emotional information and reflects it in the calculation of the matching score. For example, if a particular task is mentally demanding for the user, this will also affect the matching score.

[0727] Step 11:

[0728] Server: Saves the matching results, including the matching score, in a matching table and notifies companies and people with disabilities of the results. The optimal matching information for each user and job is provided.

[0729] Step 12:

[0730] Users: Company recruiters view the matching results through a dedicated dashboard, which displays a list of matching candidates and each candidate's matching score.

[0731] Step 13:

[0732] Users: People with disabilities can check their matching results through a dedicated dashboard, which displays a list of jobs that have been matched to them and their matching scores.

[0733] Through these steps, detailed job matching between companies and people with disabilities is carried out, providing more suitable employment opportunities. The system also takes into account the emotions of users, providing a matching process that reduces the mental burden.

[0734] Example 2

[0735] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0736] Conventional job matching systems only consider the user's abilities and limitations, but do not consider their emotional state, which means they are unable to match people in a way that reduces their mental burden. Furthermore, they are unable to properly analyze job information and break it down into individual tasks, which can result in poor job compatibility.

[0737] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for inputting job information provided by a company, an analysis means including artificial intelligence for analyzing the input job information and breaking it down into multiple individual tasks, a storage means for saving the analyzed individual tasks and their associated conditions in a database, an input means for a user to input their own abilities and limitations, a storage means for saving the input user ability and limitation information in the database, an analysis means for analyzing the user's emotional state using an emotion engine, a storage means for saving the saved user emotion information in the database, a matching means for collating the saved job information and user information to generate an optimal job match, and a notification means for notifying the company and the user of the matching result. This enables job matching that comprehensively takes into account the user's abilities, limitations, and emotional state, thereby achieving appropriate matching with reduced mental burden.

[0738] "Job information" is information that includes an overview of the work provided by a company, specific work content, and required skills and conditions.

[0739] An "input means" is a device or program that provides an interface for companies or users to input information into the system.

[0740] An "analysis means" is a device or program that includes artificial intelligence or natural language processing algorithms to process input information and break it down into multiple individual tasks.

[0741] The "storage means" is a device or program for storing analyzed information and input information in a database.

[0742] "User" means a person with a disability or their representative who uses the system to input their capabilities and limitations.

[0743] An "emotion engine" is a device or program that analyzes a user's input and facial expressions to determine their emotional state.

[0744] The "matching means" is a device or program for matching the stored job information with the user information and emotion information to generate optimal job matching.

[0745] The "notification means" is a device or program for notifying companies and users of the generated matching results.

[0746] The "matching score" is a numerical representation of the degree of compatibility between job information and user information.

[0747] The present invention is a system that not only analyzes job information provided by companies and breaks it down into tasks that can be performed by people with disabilities, but also combines it with an emotion engine that recognizes the emotions of users, thereby achieving more accurate job matching. Specific embodiments of the system are described below.

[0748] Overall system overview

[0749] The system consists of the following main functions:

[0750] 1. Entering and analyzing job information

[0751] 2. Input of the abilities and limitations of the person with a disability

[0752] 3. Emotion Recognition by Emotion Engine

[0753] 4. Job matching generation and notification

[0754] Entering and parsing job information

[0755] Terminal: A company's recruiter fills in the job details using an input form, which includes a job summary, specific job duties, and required skills and qualifications.

[0756] Examples:

[0757] A company's recruiter would enter "store management, purchasing management, staff shift management."

[0758] Server: Receives the input job information and analyzes it using a natural language processing (NLP) algorithm. Through analysis, the job information is broken down into multiple specific tasks.

[0759] Examples:

[0760] The server receives the "store management, purchasing management, staff shift management" and breaks it down into tasks such as "inventory management," "customer support," and "sales management."

[0761] Server: The decomposed tasks and their associated conditions (e.g., physical conditions and skill requirements) are stored in a database.

[0762] Input of abilities and limitations of people with disabilities

[0763] Device: People with disabilities enter the tasks they can perform and the conditions they cannot deal with into a checklist-style input form.

[0764] Examples:

[0765] A person with a disability would enter "Tasks they can do: plating," "Tasks they cannot do: carrying heavy objects," and "Limitations: using a wheelchair."

[0766] Server: Saves the entered information as a user profile in a database.

[0767] Emotion recognition by emotion engine

[0768] Terminal: Using an emotion engine, the text and facial expressions entered by the person with a disability are analyzed to determine their emotional state at the time of input (e.g., tension, anxiety, relief, etc.).

[0769] Examples:

[0770] Detects the emotional state of "slight anxiety" felt by people with disabilities when entering information into an input form.

[0771] Server: Stores the determined emotion information in a database along with the user profile.

[0772] Job matching generation and notification

[0773] Server: Matches the job details table with the user profile table to perform appropriate job matching. Checks whether the task content and conditions match the user's available tasks and restrictions.

[0774] Examples:

[0775] The server compares the tasks of "plating" and "washing dishes" with job ID 1234 with the profile of user ID 5678 and calculates a matching score. At this time, it also takes into account the "sense of security" the user feels when "plating."

[0776] Server: Stores the matching results, including the matching score, in a matching table and notifies the companies and people with disabilities of the results.

[0777] Device: Company recruiters and people with disabilities can check the matching results on their respective dashboards.

[0778] Prompt Sentence Examples

[0779] Here are some examples of prompts to input to the generative AI model:

[0780] Analyze job information entered by company recruiters and break it down into appropriate tasks. Then, perform job matching and generate matching results taking into account the abilities and limitations of the disabled persons entered. Optimize the results by also taking into account the emotional information of the disabled persons.

[0781] Through these steps, the system performs detailed job matching between companies and people with disabilities, providing more suitable employment opportunities. It also takes into account the user's feelings, providing a matching process that reduces the mental burden.

[0782] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0783] Step 1: Enter job information

[0784] Terminal: The company's recruiter enters job details into the input form, including a job summary, specific job duties, and required skills and conditions.

[0785] Input: Enter job details (e.g., "Store management, stock management, staff shift management").

[0786] Specific operation: A recruiter enters job information into a form on the terminal, and the information is sent to the server.

[0787] Step 2: Job information analysis and task decomposition

[0788] Server: The server receives the job information, analyzes it using a natural language processing (NLP) algorithm, and breaks down the analysis results into multiple specific tasks.

[0789] Input: Received job information.

[0790] Data processing / calculation: Job information is analyzed using natural language processing and broken down into individual tasks.

[0791] Output: Decomposed task information (e.g., "Inventory management," "Customer support," "Sales management").

[0792] Specific operation: The server breaks down "store management, purchasing management, staff shift management" into "inventory management," "customer support," and "sales management."

[0793] Step 3: Save task information

[0794] Server: Stores the decomposed task information and its associated conditions (e.g., physical conditions and skill requirements) in a database.

[0795] Input: Decomposed task information.

[0796] Data processing / calculation: Task information and conditions are associated and saved in the database.

[0797] Output: The saved database entries.

[0798] Specific operation: Assign conditions such as "basic arithmetic ability" and "interpersonal skills" to "inventory management" and store this information in a database.

[0799] Step 4: Enter the abilities and limitations of the person with a disability

[0800] Device: People with disabilities enter the tasks they can perform and the conditions they cannot deal with into a checklist-style input form.

[0801] Input: Information about the abilities and limitations of the person with a disability (e.g., "Tasks that can be done: plating food," "Tasks that cannot be done: lifting heavy objects," "Limitations: using a wheelchair").

[0802] Specific operation: A person with a disability enters their abilities and limitations into a form on the device, and that information is sent to the server.

[0803] Step 5: Save your user profile

[0804] Server: The entered information about the abilities and limitations of the disabled person is saved in a database as a user profile.

[0805] Input: Disability ability and limitation information.

[0806] Data processing / calculation: Convert the input information into a profile format and save it in the database.

[0807] Output: The saved user profile.

[0808] Specific actions: Information on "serving food," "carrying heavy objects," and "using a wheelchair" is stored in a database.

[0809] Step 6: Emotion Recognition with the Emotion Engine

[0810] Device: An emotion engine is used to analyze the text and facial expressions of people with disabilities as they type, thereby determining their emotional state (e.g., tension, anxiety, relief, etc.) at the time of input.

[0811] Input: Input and facial expression data from the person with a disability.

[0812] Data processing / calculation: The emotion engine analyzes input content and facial expressions to determine the emotional state.

[0813] Output: Determined emotion information (e.g., "anxiety").

[0814] Specific operation: The system detects "anxiety" from the facial expressions and writing of people with disabilities.

[0815] Step 7: Storing Emotional Information

[0816] Server: Stores the determined emotion information in a database along with the user profile.

[0817] Input: Determined emotion information.

[0818] Data processing / calculation: Emotional information is added to the user profile and stored in the database.

[0819] Output: The updated user profile.

[0820] Specific behavior: Save the emotional information "anxiety" along with the profile data.

[0821] Step 8: Match job details with user profile

[0822] Server: Matches the job details table with the user profile table to perform appropriate job matching. Checks whether the task content and conditions match the user's available tasks and restrictions.

[0823] Input: Job details and user profile information.

[0824] Data processing / calculation: Compare job details with user profile and calculate compatibility.

[0825] Output: Matching results and matching score (e.g., matching score of 85 for the tasks "plating" and "washing dishes").

[0826] Specific operation: The server matches the tasks "plating" and "washing dishes" of job ID 1234 with the profile of user ID 5678 and calculates the matching score.

[0827] Step 9: Notification of Matching Results

[0828] Server: Stores the matching results, including the matching score, in a matching table and notifies the companies and people with disabilities of the results.

[0829] Input: Matching results and matching scores.

[0830] Data processing / calculation: The matching results and matching scores are stored as a set in the matching table, and a notification message is generated.

[0831] Output: Notification message (e.g., "Matching result: Job ID 1234, score 85").

[0832] Specific operation: The matching score of 85 is saved in the database and notified to the company and the person with a disability.

[0833] Step 10: Check the results

[0834] Device: Company recruiters and people with disabilities can view matching results on their dashboards.

[0835] Input: Your dashboard login details.

[0836] Output: A screen showing the matching results and matching scores.

[0837] What it does: Corporate recruiters and people with disabilities can view matched candidates and their matching scores on a dashboard.

[0838] Through these processing steps, the system performs detailed job matching between companies and people with disabilities, providing appropriate employment opportunities. It also takes into account the user's feelings, making it possible to provide a matching process that reduces the mental burden.

[0839] (Application example 2)

[0840] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0841] It is necessary to improve the work efficiency of people with disabilities working in factories while reducing their mental burden. In particular, there is a need to achieve more accurate job matching by breaking down job information into tasks that are appropriate for the abilities of people with disabilities and by taking into account their emotional state at the time. It is also important to provide an environment where people with disabilities can work in real time in an emotionally appropriate state.

[0842] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0843] In this invention, the server includes: an input means for inputting job information provided by a company; an analysis means including artificial intelligence for analyzing the input job information and breaking it down into multiple individual tasks; a storage means for saving the analyzed individual tasks and their associated conditions in a database; an input means for a user to input their own abilities and limitations; a storage means for saving the input user's ability and limitation information in the database; a matching means for collating the saved job information with user information to generate an optimal job match; a notification means for notifying the company and the user of the matching results; an emotion engine that recognizes the user's emotional state; a storage means for saving the emotion information recognized by the emotion engine in a profile; and a matching means for calculating a matching score taking the user's emotion information into consideration. This allows individuals with disabilities to be assigned tasks that are suited to their abilities and to work with less mental strain.

[0844] An "input means" is a device or method for receiving data. It typically includes a keyboard, mouse, touch screen, voice input device, etc.

[0845] "Analysis means" refers to a device or method for breaking down input data and understanding its meaning and structure. This includes artificial intelligence and natural language processing algorithms.

[0846] "Artificial intelligence" is a technology that allows computer systems to imitate human intellectual behavior and make judgments and learn.

[0847] "Storage" means a device or method for long-term storage of data. This includes databases and cloud storage.

[0848] A "database" is a structured collection of data that is systematically organized, stored, and can be efficiently searched and updated.

[0849] A "matching means" is a device or method for comparing different data to evaluate the degree of agreement or compatibility.

[0850] "Notification medium" means a device or method for communicating information to a specific person or system, including email, SMS, in-app notifications, etc.

[0851] An "emotion engine" is a device or method for analyzing and identifying a user's emotional state. It includes technologies such as facial expression recognition and voice analysis.

[0852] A "profile" is a collection of information about a particular user, including their capabilities, limitations, emotional state, etc.

[0853] A "matching score" is a numerical representation of the degree of suitability or agreement of the matching result. For example, it may include an evaluation score out of 100 points.

[0854] This invention is a system that improves the work efficiency and reduces the mental burden of disabled workers in factories. The system includes the following main components and functions:

[0855] 1. Entering and analyzing job information

[0856] Company processing

[0857] The server provides input means for company recruiters to enter job details. This input means can include a text input form or a voice input device. The entered job information is received by the server and broken down into multiple individual tasks using a natural language processing (NLP) algorithm. The analyzed individual tasks are then stored in a database.

[0858] 2. Input of the abilities and limitations of the person with a disability

[0859] Processing for people with disabilities

[0860] The device provides an input method for people with disabilities to enter their capabilities and limitations. This input method can be a checklist-style form or a touchscreen. The information entered is stored in a database as a user profile.

[0861] 3. Emotion Recognition by Emotion Engine

[0862] Emotion recognition processing

[0863] The device uses an emotion engine to analyze the text and facial expressions entered by users with disabilities. This emotion engine uses hardware such as a facial recognition camera and a voice analyzer, as well as software such as EmotionRecognizer. The emotional information that is identified is stored in a database along with the user profile.

[0864] 4. Job matching generation and notification

[0865] Matching process

[0866] The server compares the job details table with the user profile table to perform appropriate job matching. It checks whether the task content and conditions match the user's available tasks and constraints. It also calculates a matching score taking into account the user's emotional information. The calculation results are saved in the matching table and notified to the company and the person with a disability.

[0867] Specific examples

[0868] If a disabled factory worker inputs "I'll do my best today," the emotion recognition engine will detect positive emotions such as "relief." When job information such as "store management, purchasing management, and staff shift management" is given, this information is broken down into tasks such as "inventory management," "customer service," and "sales management." The broken down tasks are then compared with the user profile to match the most suitable tasks.

[0869] Prompt Sentence Examples

[0870] Job information: Store management, purchasing management, staff shift management

[0871] Emotion input: I'll do my best today too

[0872] User profile: Possible tasks: Inventory management, sales management; Impossible tasks: Customer support

[0873] This system allows people with disabilities to be assigned tasks that suit their abilities, allowing them to work with less mental strain.

[0874] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0875] Step 1:

[0876] A company's recruiter uses a terminal to input job information. Input methods include text input forms and voice input devices. Job details such as "store management, purchasing management, and staff shift management" are entered. The server receives the input job information and temporarily stores it in a database.

[0877] Input: Job information (text or audio format)

[0878] Output: Saved job information

[0879] Step 2:

[0880] The server analyzes the input job information using a natural language processing (NLP) algorithm and breaks it down into multiple individual tasks. For example, job information such as "store management, purchasing management, and staff shift management" is broken down into specific tasks such as "inventory management," "customer service," and "sales management." Each broken down task is assigned related conditions (such as required skills and physical conditions) and stored in a database.

[0881] Input: Job information

[0882] Output: Analyzed individual tasks and associated conditions

[0883] Step 3:

[0884] The terminal provides an input means for people with disabilities to enter their abilities and limitations. To do this, people with disabilities use a checklist-style form or a touch screen to enter information such as "possible task: serving food," "impossible task: carrying heavy objects," and "limitations: using a wheelchair." The entered ability and limitation information is received by the server and stored in a database as a user profile.

[0885] Input: Disability capabilities and limitations information

[0886] Output: Saved user profile

[0887] Step 4:

[0888] The device uses an emotion engine to analyze the text and facial expressions entered by the person with a disability. For example, if a person with a disability enters "I'll do my best today," the emotion engine analyzes their facial expression and tone of voice to identify positive emotions such as "relief." The recognized emotion information is then added to a profile by the server.

[0889] Input: Text and facial expression data of a person with a disability

[0890] Output: Parsed emotion information

[0891] Step 5:

[0892] The server compares the stored job information with the user profile to generate optimal job matching. Task content and conditions are matched based on the user's available tasks and constraints. Furthermore, the server also considers the user's emotional information and calculates a matching score to minimize mental strain. For example, if a particular task is mentally stressful for the user, the score for that task will be reduced.

[0893] Input: Job information, user profile, emotion information

[0894] Output: Matching score and matching result

[0895] Step 6:

[0896] The server notifies the company and the person with a disability of the matching results via email, SMS, in-app notifications, etc. The company's recruiter and the person with a disability can check the matching results on their dashboard and receive instructions for performing the appropriate tasks.

[0897] Input: Matching results

[0898] Output: Notified matching results

[0899] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0900] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0901] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0902] [Third embodiment]

[0903] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0904] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0905] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0906] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0907] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0908] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0909] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0910] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0911] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0912] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0913] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0914] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0915] The present invention is a system that realizes optimal job matching by analyzing job information provided by companies and breaking it down into tasks that can be performed by people with disabilities. Specific embodiments of the system are described below.

[0916] Overall system overview

[0917] The system consists of the following main functions:

[0918] 1. Entering and analyzing job information

[0919] 2. Input of the abilities and limitations of the person with a disability

[0920] 3. Job matching generation and notification

[0921] 1. Entering and analyzing job information

[0922] Company processing

[0923] Terminal: Provides a form for company recruiters to enter job details in natural language, including a job summary, specific job duties, and required skills and qualifications.

[0924] Server: Once job information is input, it uses natural language processing (NLP) algorithms and machine learning models to analyze it, which breaks it down into multiple specific tasks.

[0925] Server: Each decomposed task and its associated conditions (e.g., physical conditions and skill requirements) are stored in a database.

[0926] Examples:

[0927] When a company recruiter inputs "store management, purchasing management, and staff shift management," the AI ​​analyzes this and breaks it down into tasks such as "inventory management," "customer service," and "sales management." Each task is assigned a requirement such as "basic arithmetic ability" and "interpersonal skills."

[0928] 2. Input of the abilities and limitations of the person with a disability

[0929] Processing for people with disabilities

[0930] Device: Provides a checklist-style form for people with disabilities to enter their capabilities and limitations, including tasks they can perform and conditions they cannot accommodate.

[0931] Server: The information entered is stored in a database as a user profile.

[0932] Examples:

[0933] When a person with a disability enters "Tasks they can do: plating food," "Tasks they cannot do: carrying heavy objects," and "Restrictions: using a wheelchair," that information is saved in a database.

[0934] 3. Job matching generation and notification

[0935] Matching process

[0936] Server: Matches the job details table with the user profile table and generates matching candidates based on matching tasks and conditions.

[0937] Server: Calculates the matching score and generates the best job matching based on it. The matching score is determined by the compatibility of the task and the user's skills and constraints.

[0938] Server: Stores the matching results in a database and notifies companies and people with disabilities of the results.

[0939] Examples:

[0940] The server compares the tasks of "plating" and "washing dishes" with job ID 1234 with the profile of user ID 5678 and calculates a matching score. If the score is 85, the result is saved in the database and notified to the company and the person with a disability.

[0941] Checking the results

[0942] Device: Company recruiters and people with disabilities can view matching results on their dashboards.

[0943] On your device: The dashboard displays your matches and their matching scores.

[0944] In this way, this system analyzes companies' job information in detail and matches jobs that suit the abilities and limitations of people with disabilities, aiming to increase employment opportunities for people with disabilities and reduce turnover rates.

[0945] The processing flow will be explained below.

[0946] Step 1:

[0947] User: A company's recruiter enters job information in natural language into the automated job decomposition system's input form. This information includes a job summary, specific job duties, and required skills and conditions.

[0948] Step 2:

[0949] Server: Receives input job information and passes it to a natural language processing (NLP) algorithm, which parses the job information and breaks it down into multiple individual tasks based on templates.

[0950] Step 3:

[0951] Server: The server uses machine learning models to refine the analyzed tasks and estimate the requirements for each task (e.g., specific skills or physical abilities). This determines the requirements for each task.

[0952] Step 4:

[0953] Server: Stores the decomposed tasks and their associated condition information in the task details table for later collation and matching.

[0954] Step 5:

[0955] User: A person with a disability enters information about the tasks and limitations they can perform in the form of a checklist. The checklist lists specific tasks and limitations, and the user selects which ones they can perform.

[0956] Step 6:

[0957] Server: Receives the information entered by the person with a disability and stores it in a user profile table, including the tasks they can perform and their limitations.

[0958] Step 7:

[0959] Server: Checks the stored job details table against the user profile table to perform appropriate job matching, specifically checking whether the task content and conditions match the user's available tasks and restrictions.

[0960] Step 8:

[0961] Server: Calculates a matching score based on the compatibility between the job and the user. The matching score is determined by the degree to which each task matches the user's skills and constraints.

[0962] Step 9:

[0963] Server: Saves the matching results, including the matching score, in a matching table and notifies companies and people with disabilities of the results. The optimal matching information for each user and job is provided.

[0964] Step 10:

[0965] Users: Company recruiters view the matching results through a dedicated dashboard, which displays a list of matching candidates and each candidate's matching score.

[0966] Step 11:

[0967] Users: People with disabilities can check their matching results through a dedicated dashboard, which displays a list of jobs that have been matched to them and their matching scores.

[0968] Through these steps, detailed job matching will be carried out between companies and people with disabilities, providing more appropriate employment opportunities.

[0969] Example 1

[0970] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0971] In recent years, companies have been providing a wide variety of job information, but it is difficult for people with disabilities to find tasks that they can perform appropriately. It is also difficult for people with disabilities themselves to find jobs that suit their abilities and limitations, which reduces employment opportunities and contributes to high turnover rates. Current systems often lack sufficient analysis of job information and do not properly generate or match task lists suitable for people with disabilities. Therefore, there is a need for an effective system that allows people with disabilities to find jobs that suit them and companies to hire the right personnel.

[0972] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0973] In this invention, the server includes an input means for inputting job information provided by a company, an analysis means including artificial intelligence for analyzing the input job information and breaking it down into multiple individual tasks, a storage means for saving the analyzed individual tasks and their associated conditions in a database, an input means for a user to input their own abilities and limitations, a storage means for saving the input user ability and limitation information in the database, a comparison means for comparing the saved job information with user information to generate optimal job matching, a notification means for notifying the company and user of the comparison results, and a display means for displaying the comparison results on a dashboard. This enables detailed analysis of company job information and job matching that is appropriate for the abilities and limitations of people with disabilities.

[0974] "Company" refers to an organization that provides job information and conducts recruitment activities.

[0975] "Job information" refers to information provided by companies, such as job content, required skills, conditions, etc.

[0976] "Input means" refers to an interface through which a user inputs text and options.

[0977] The "analysis means" is a system that uses artificial intelligence to analyze input job information and break it down into multiple individual tasks.

[0978] "Artificial intelligence" is a technology that uses natural language processing and machine learning models to analyze and classify data.

[0979] "Storage means" refers to a system that stores analyzed data and input information in a database.

[0980] "User" refers to a person with a disability who uses the system.

[0981] "Ability" refers to the tasks a user can perform and the skills they possess.

[0982] "Limitations" refers to constraints such as tasks that a user cannot perform or physical conditions that the user has.

[0983] The "matching means" is a system that generates optimal job matching based on the stored job information and user information.

[0984] "Notification means" is a system for notifying companies and users of the matching results.

[0985] A "display means" is a system that visually displays information to a user through an interface such as a dashboard.

[0986] The present invention is a system that realizes optimal job matching by analyzing job information provided by companies and breaking it down into tasks that can be performed by people with disabilities. Specific embodiments of the system are described below.

[0987] System Overview

[0988] The system consists of the following main hardware and software components:

[0989] Devices: Computers, smartphones, or other devices used by company recruiters and people with disabilities to enter information.

[0990] Server: A computer system that analyzes input data and stores, collates, and notifies users. Specific examples include Apache and Nginx servers.

[0991] Database: A database system for storing analyzed job information and user profiles. Specific examples include MySQL and PostgreSQL.

[0992] Artificial intelligence models: Natural language processing (NLP) algorithms and machine learning models used to parse job information and break it down into tasks. Specific examples include Python's NLTK, SpaCy, TensorFlow, and Scikit-learn.

[0993] Specific processing flow

[0994] 1. Entering and analyzing job information

[0995] Terminal: A company's recruiter enters job details into an input form, which includes a job summary, specific job duties, and required skills and conditions.

[0996] Example: A recruiter enters "store management, purchasing management, staff shift management."

[0997] Server: Once job information is entered, it is analyzed using natural language processing (NLP) algorithms and machine learning models. As a result of the analysis, the job information is broken down into multiple specific tasks.

[0998] Example: The server breaks down job information into tasks such as "inventory management," "customer support," and "sales management."

[0999] Server: Each decomposed task and its associated conditions (e.g., physical conditions and skill requirements) are stored in a database.

[1000] 2. Input of the abilities and limitations of the person with a disability

[1001] Device: People with disabilities enter their capabilities and limitations using a checklist-style form, which lists the tasks they can perform and the conditions they cannot accommodate.

[1002] Example: A person with a disability enters "Tasks I can do: Placing food on the table," "Tasks I cannot do: Carrying heavy objects," and "Restrictions: Using a wheelchair."

[1003] Server: The entered information is stored in a database as a user profile.

[1004] 3. Job matching generation and notification

[1005] Server: Compares the job details table with the user profile table and generates matching candidates based on compatible tasks and conditions. Specifically, it uses natural language processing and machine learning models to calculate the compatibility between tasks and user profiles.

[1006] Example: The server matches the "plating" task with the user's profile and calculates a matching score.

[1007] Server: Generates optimal job matches based on the matching scores, stores the results in a database, and notifies companies and people with disabilities of the results.

[1008] 4. Check the results

[1009] Device: Corporate recruiters and people with disabilities can check their matching results on their own dashboard.

[1010] Example: Companies and people with disabilities evaluate the matching results confirmed through the dashboard and take the following actions:

[1011] Prompt Sentence Examples

[1012] Analyze job information entered by companies, break it down into specific tasks, and compare it with the abilities and limitations entered by individuals with disabilities to generate an appropriate job matching score.

[1013] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1014] Step 1:

[1015] The terminal provides an input form for company recruiters to enter job details. The recruiter inputs the job summary, specific work content, required skills and conditions in natural language. This input sends the job information to the server. Input data includes "store management, purchasing management, staff shift management," etc.

[1016] Step 2:

[1017] The server stores the received job information in a temporary database, which is used for later analysis. The stored data is the entire job information entered.

[1018] Step 3:

[1019] The server begins to analyze the stored job information. Using natural language processing (NLP) algorithms (such as Python's NLTK or SpaCy) and machine learning models (such as TensorFlow or Scikit-learn), it analyzes the job information and breaks it down into multiple specific tasks. The input data is the entire job information, and the output data is the broken down task list and corresponding conditions. For example, the job information is broken down into the tasks "inventory management," "customer support," and "sales management."

[1020] Step 4:

[1021] The server stores each decomposed task and its associated conditions in a database. The stored data includes detailed information about each task (e.g., "basic arithmetic ability" for "inventory management" and "interpersonal skills" for "customer service").

[1022] Step 5:

[1023] The device provides a checklist-style input form for people with disabilities to enter their abilities and limitations. People with disabilities enter the tasks they can do and the conditions they cannot handle. This input creates a user profile, which is sent to the server. Input data includes such things as "Tasks they can do: plating food," "Tasks they cannot do: carrying heavy objects," and "Limitations: using a wheelchair."

[1024] Step 6:

[1025] The server stores the data received from the disabled person in a temporary database, which is later used for matching purposes. The stored data is the entire entered user profile.

[1026] Step 7:

[1027] The server compares the saved job information with the user profile and generates matching candidates based on compatible tasks and conditions. This uses natural language processing and machine learning models, with the input data being the job details table and user profile table, and the output data being the matching candidates. The server calculates the compatibility between the task and the user's skills and restrictions, and calculates a matching score. As a specific example, the task "plating" is compared with the user's profile, and the matching score is calculated as 75 points.

[1028] Step 8:

[1029] The server stores the matching results in a database and notifies the company and the person with a disability of the results. The stored data is the matching score and the corresponding task list, and the notification includes the job ID, user ID, and compatibility score.

[1030] Step 9:

[1031] The device provides an interface for corporate recruiters and people with disabilities to check matching results on their own dashboards. The data displayed is the matched candidates and their matching scores. For example, the dashboard might show that "User ID 5678 matches Job ID 1234 with a matching score of 75."

[1032] (Application example 1)

[1033] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1034] Previously, there were systems that analyzed job information provided by companies and matched them with tasks suitable for people with disabilities, but these systems did not support real-time task notifications or execution support, making it difficult for people with disabilities to continuously perform appropriate tasks at work sites such as logistics centers.In addition, people with disabilities could not easily recognize or understand the optimal tasks according to their own situation, making it difficult to increase employment opportunities and achieve efficient work.

[1035] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1036] In this invention, the server includes: an input means for inputting job information provided by a company; an analysis means including artificial intelligence for analyzing the input job information and breaking it down into multiple individual tasks; a storage means for saving the analyzed individual tasks and their associated conditions in a database; an input means for a user to input their own abilities and limitations; a storage means for saving the input user ability and limitation information in the database; a matching means for collating the saved job information and user information to generate optimal job matching; a notification means for notifying the company and the user of the matching results; and a head-mounted display including a display device for displaying the notified tasks in real time and supporting their completion. This enables people with disabilities at logistics centers to recognize and appropriately complete the tasks that are optimal for them in real time.

[1037] An "enterprise" is an organization that conducts business, such as a company or corporation.

[1038] "Job information" refers to information provided by a company, such as the business content, job details, required skills and conditions, etc.

[1039] "Input means" means a device or software for inputting information into a system.

[1040] "Analysis means" refers to a device or software that breaks down input information and extracts meaning.

[1041] "Artificial intelligence" is a technology that uses machine learning and natural language processing to analyze data and solve problems.

[1042] "Storage means" refers to a device or software for storing data for a certain period of time.

[1043] A "database" is a system for efficiently storing, managing, and searching data.

[1044] "User" refers to any person, including a person with a disability, who uses the system and receives tasks.

[1045] "Ability" refers to the skills and tasks that a user can perform.

[1046] "Limitations" refer to skills or tasks that a user cannot perform.

[1047] The "matching means" refers to a device or software that compares the stored job information with the user information and derives the optimal match.

[1048] "Notification means" means a device or software for notifying users of match results or other information.

[1049] A "head-mounted display" is a device worn on the head to display information.

[1050] "Real-time" refers to processing and information exchange occurring instantly with little or no delay.

[1051] Overall system overview

[1052] This invention is a system for efficiently matching tasks for people with disabilities in logistics centers. The system inputs and analyzes job information, inputs the abilities and limitations of people with disabilities, generates and notifies job matching, and provides real-time task notification and execution support.

[1053] 1. Entering and analyzing job information

[1054] The company's terminal has an input means for entering job information. The entered job information is analyzed by the server. Natural language processing (NLP) and machine learning models are used for the analysis. This breaks down the job information into multiple individual tasks. The analyzed tasks and their associated conditions are stored in a database by the server.

[1055] For example, if a company recruiter inputs "stock organization, packing, and product movement," the AI ​​will break this down into "inventory management," "packing work," and "transportation work." Each task will be assigned a condition such as "basic arithmetic ability" or "manual dexterity."

[1056] 2. Input of the abilities and limitations of the person with a disability

[1057] The device on the disabled person's side has a checklist-style input means for entering their abilities and limitations. The input information is saved in a database as a user profile, which clarifies the tasks that the disabled person can perform and their limitations.

[1058] For example, if a person with a disability enters "Tasks they can do: picking," "Tasks they cannot do: working at heights," and "Limitations: using a wheelchair," that information is saved in the database.

[1059] 3. Job matching generation and notification

[1060] The server uses a matching method to match job information with user profiles and generate optimal job matches. The matching score is determined by the compatibility of the task with the user's skills and limitations. The matching results are stored in a database by the server and notified to companies and people with disabilities.

[1061] As a concrete example, the server compares the "picking" and "packing" tasks with job ID 1234 with the profile of user ID 5678 and calculates a matching score. If the score is 85, the result is saved in the database and notified to the company and the person with a disability.

[1062] 4. Real-time task notifications and assistance

[1063] The matching results are notified to the person with a disability in real time via a head-mounted display (e.g., HMD). The HMD displays the notified tasks in real time and provides instructions to assist in their completion. This streamlines task management within the logistics center and enables people with disabilities to perform tasks optimally.

[1064] As a concrete example, a person with a disability can be notified in real time, "Your next task is picking. Please take the product from the designated shelf," and can then follow the instructions to carry out the task.

[1065] Prompt Sentence Examples

[1066] Here are some examples of prompts to input to a generative AI model:

[1067] text

[1068] Consider a detailed design proposal for a system that matches the abilities of people with disabilities with job information. The system uses natural language processing to analyze job information and break it down into specific tasks. It also inputs each user's profile and matches it with job information to suggest the most suitable job.

[1069] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1070] Step 1:

[1071] Entering job information

[1072] How it works: A company recruiter enters job information in natural language on a terminal.

[1073] Input: Job summary, specific job duties, required skills and conditions.

[1074] Output: Raw job information sent to the server.

[1075] Specific operation: The company enters the job details as "Pick, pack, and move goods."

[1076] Step 2:

[1077] Job Information Analysis

[1078] How it works: The server analyzes the input job information using natural language processing (NLP) and breaks it down into multiple individual tasks.

[1079] Input: Unparsed job information.

[1080] Output: Analyzed individual tasks and associated conditions stored in a database.

[1081] Specific operation: The server breaks down the "picking and packing" job into "inventory management," "packing work," and "transportation work," and assigns conditions such as "basic arithmetic ability" and "manual dexterity" to each.

[1082] Step 3:

[1083] Entering user capabilities and limitations

[1084] How it works: A person with a disability enters their abilities and limitations in a checklist format on a terminal.

[1085] Input: Tasks that can be performed and conditions that cannot be met.

[1086] Output: Profile information of disabled people stored in a database.

[1087] Specific actions: A person with a disability enters "Tasks they can do: picking items," "Tasks they cannot do: working at heights," and "Restrictions: using a wheelchair."

[1088] Step 4:

[1089] Job Matching Generation

[1090] Operation: The server compares the stored job information with the user's capabilities and restrictions to generate the optimal job matching.

[1091] Input: Parsed job information, user profile.

[1092] Output: Matching results and matching scores.

[1093] Specific operation: The server matches the "picking" and "packing" of job ID 1234 with the profile of user ID 5678 and calculates a matching score of 85.

[1094] Step 5:

[1095] Generate and send notifications

[1096] Operation: The server stores the matching results in a database and notifies the company and the person with a disability.

[1097] Input: Job matching results.

[1098] Output: Notifications displayed on corporate and disability devices.

[1099] Specific action: The server sends a notification saying "User ID 5678 matches job ID 1234."

[1100] Step 6:

[1101] Real-time notifications and assistance

[1102] How it works: A person with a disability wears a head-mounted display (HMD) and performs tasks displayed in real time.

[1103] Input: Real-time task notifications from the server.

[1104] Output: Task instructions displayed during execution.

[1105] Specific actions: A person with a disability puts on the HMD and follows the instructions displayed, such as, "The next task is picking. Please take the product from the designated shelf."

[1106] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1107] The present invention is a system that not only analyzes job information provided by companies and breaks it down into tasks that can be performed by people with disabilities, but also combines it with an emotion engine that recognizes the emotions of users, thereby achieving more accurate job matching. Specific embodiments of the system are described below.

[1108] Overall system overview

[1109] The system consists of the following main functions:

[1110] 1. Entering and analyzing job information

[1111] 2. Input of the abilities and limitations of the person with a disability

[1112] 3. Emotion Recognition by Emotion Engine

[1113] 4. Job matching generation and notification

[1114] 1. Entering and analyzing job information

[1115] Company processing

[1116] Terminal: Provides a form for company recruiters to enter job details in natural language, including a job summary, specific job duties, and required skills and qualifications.

[1117] Server: Once job information is input, it uses natural language processing (NLP) algorithms and machine learning models to analyze it, which breaks it down into multiple specific tasks.

[1118] Server: Each decomposed task and its associated conditions (e.g., physical conditions and skill requirements) are stored in a database.

[1119] Examples:

[1120] When a company recruiter inputs "store management, purchasing management, and staff shift management," the AI ​​analyzes this and breaks it down into tasks such as "inventory management," "customer service," and "sales management." Each task is assigned a requirement such as "basic arithmetic ability" and "interpersonal skills."

[1121] 2. Input of the abilities and limitations of the person with a disability

[1122] Processing for people with disabilities

[1123] Device: Provides a checklist-style form for people with disabilities to enter their capabilities and limitations, including tasks they can perform and conditions they cannot accommodate.

[1124] Server: The information entered is stored in a database as a user profile.

[1125] Examples:

[1126] When a person with a disability enters "Tasks they can do: plating food," "Tasks they cannot do: carrying heavy objects," and "Restrictions: using a wheelchair," that information is saved in a database.

[1127] 3. Emotion Recognition by Emotion Engine

[1128] Emotion recognition processing

[1129] Device: An emotion engine is used to analyze the text and facial expressions of people with disabilities as they type, thereby determining their emotional state (e.g., tension, anxiety, relief, etc.) at the time of input.

[1130] Server: The determined emotional information is stored in a database along with the disabled person's profile.

[1131] Examples:

[1132] If a person with a disability feels "a little anxious" when filling out a form, that emotional information will also be saved.

[1133] 4. Job matching generation and notification

[1134] Matching process

[1135] Server: Checks the job details table against the user profile table to perform appropriate job matching. Specifically, it checks whether the task content and conditions match the user's available tasks and restrictions.

[1136] Server: The server also takes into account the user's emotional information and reflects it in the calculation of the matching score. For example, if a particular task is mentally demanding for the user, this will also affect the matching score.

[1137] Server: Saves the matching results, including the matching score, in a matching table and notifies companies and people with disabilities of the results. The optimal matching information for each user and job is provided.

[1138] Examples:

[1139] The server compares the tasks of "plating" and "washing dishes" with job ID 1234 with the profile of user ID 5678 and calculates a matching score. The server also takes into account the "sense of security" the user feels when "plating." If the score is 85, the result is saved in the database and notified to the company and the person with a disability.

[1140] Checking the results

[1141] Device: Company recruiters and people with disabilities can view matching results on their dashboards.

[1142] On your device: The dashboard displays your matches and their matching scores.

[1143] Through these steps, detailed job matching between companies and people with disabilities is carried out, providing more suitable employment opportunities. The system also takes into account the emotions of users, providing a matching process that reduces the mental burden.

[1144] The processing flow will be explained below.

[1145] Step 1:

[1146] User: A company's recruiter enters job information in natural language into the automated job decomposition system's input form. This information includes a job summary, specific job duties, and required skills and conditions.

[1147] Step 2:

[1148] Server: Receives input job information and passes it to a natural language processing (NLP) algorithm, which parses the job information and breaks it down into multiple individual tasks based on templates.

[1149] Step 3:

[1150] Server: The server uses machine learning models to refine the analyzed tasks and estimate the requirements for each task (e.g., specific skills or physical abilities). This determines the requirements for each task.

[1151] Step 4:

[1152] Server: Stores the decomposed tasks and their associated condition information in the task details table for later collation and matching.

[1153] Step 5:

[1154] User: A person with a disability enters information about the tasks and limitations they can perform in the form of a checklist. The checklist lists specific tasks and limitations, and the user selects which ones they can perform.

[1155] Step 6:

[1156] Device: When a person with a disability uses an input form, an emotion engine runs in the background, analyzing facial expressions and text in real time as they enter information.

[1157] Step 7:

[1158] Server: Receives the emotional data analyzed by the emotion engine, associates it with the user profile, and stores it in a database, along with the emotional state at the time of input.

[1159] Step 8:

[1160] Server: Receives task and emotion information entered by users with disabilities and stores it in a user profile table. The stored information includes tasks that can be performed, limitations, and emotion data at the time of input.

[1161] Step 9:

[1162] Server: Checks the job details table against the user profile table to perform appropriate job matching, specifically checking whether the task content and conditions match the user's available tasks and restrictions.

[1163] Step 10:

[1164] Server: The server also takes into account the user's emotional information and reflects it in the calculation of the matching score. For example, if a particular task is mentally demanding for the user, this will also affect the matching score.

[1165] Step 11:

[1166] Server: Saves the matching results, including the matching score, in a matching table and notifies companies and people with disabilities of the results. The optimal matching information for each user and job is provided.

[1167] Step 12:

[1168] Users: Company recruiters view the matching results through a dedicated dashboard, which displays a list of matching candidates and each candidate's matching score.

[1169] Step 13:

[1170] Users: People with disabilities can check their matching results through a dedicated dashboard, which displays a list of jobs that have been matched to them and their matching scores.

[1171] Through these steps, detailed job matching between companies and people with disabilities is carried out, providing more suitable employment opportunities. The system also takes into account the emotions of users, providing a matching process that reduces the mental burden.

[1172] Example 2

[1173] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1174] Conventional job matching systems only consider the user's abilities and limitations, but do not consider their emotional state, which means they are unable to match people in a way that reduces their mental burden. Furthermore, they are unable to properly analyze job information and break it down into individual tasks, which can result in poor job compatibility.

[1175] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for inputting job information provided by a company, an analysis means including artificial intelligence for analyzing the input job information and breaking it down into multiple individual tasks, a storage means for saving the analyzed individual tasks and their associated conditions in a database, an input means for a user to input their own abilities and limitations, a storage means for saving the input user ability and limitation information in the database, an analysis means for analyzing the user's emotional state using an emotion engine, a storage means for saving the saved user emotion information in the database, a matching means for collating the saved job information and user information to generate an optimal job match, and a notification means for notifying the company and the user of the matching result. This enables job matching that comprehensively takes into account the user's abilities, limitations, and emotional state, thereby achieving appropriate matching with reduced mental burden.

[1176] "Job information" is information that includes an overview of the work provided by a company, specific work content, and required skills and conditions.

[1177] An "input means" is a device or program that provides an interface for companies or users to input information into the system.

[1178] An "analysis means" is a device or program that includes artificial intelligence or natural language processing algorithms to process input information and break it down into multiple individual tasks.

[1179] The "storage means" is a device or program for storing analyzed information and input information in a database.

[1180] "User" means a person with a disability or their representative who uses the system to input their capabilities and limitations.

[1181] An "emotion engine" is a device or program that analyzes a user's input and facial expressions to determine their emotional state.

[1182] The "matching means" is a device or program for matching the stored job information with the user information and emotion information to generate optimal job matching.

[1183] The "notification means" is a device or program for notifying companies and users of the generated matching results.

[1184] The "matching score" is a numerical representation of the degree of compatibility between job information and user information.

[1185] The present invention is a system that not only analyzes job information provided by companies and breaks it down into tasks that can be performed by people with disabilities, but also combines it with an emotion engine that recognizes the emotions of users, thereby achieving more accurate job matching. Specific embodiments of the system are described below.

[1186] Overall system overview

[1187] The system consists of the following main functions:

[1188] 1. Entering and analyzing job information

[1189] 2. Input of the abilities and limitations of the person with a disability

[1190] 3. Emotion Recognition by Emotion Engine

[1191] 4. Job matching generation and notification

[1192] Entering and parsing job information

[1193] Terminal: A company's recruiter fills in the job details using an input form, which includes a job summary, specific job duties, and required skills and qualifications.

[1194] Examples:

[1195] A company's recruiter would enter "store management, purchasing management, staff shift management."

[1196] Server: Receives the input job information and analyzes it using a natural language processing (NLP) algorithm. Through analysis, the job information is broken down into multiple specific tasks.

[1197] Examples:

[1198] The server receives the "store management, purchasing management, staff shift management" and breaks it down into tasks such as "inventory management," "customer support," and "sales management."

[1199] Server: The decomposed tasks and their associated conditions (e.g., physical conditions and skill requirements) are stored in a database.

[1200] Input of abilities and limitations of people with disabilities

[1201] Device: People with disabilities enter the tasks they can perform and the conditions they cannot deal with into a checklist-style input form.

[1202] Examples:

[1203] A person with a disability would enter "Tasks they can do: plating," "Tasks they cannot do: carrying heavy objects," and "Limitations: using a wheelchair."

[1204] Server: Saves the entered information as a user profile in a database.

[1205] Emotion recognition by emotion engine

[1206] Terminal: Using an emotion engine, the text and facial expressions entered by the person with a disability are analyzed to determine their emotional state at the time of input (e.g., tension, anxiety, relief, etc.).

[1207] Examples:

[1208] Detects the emotional state of "slight anxiety" felt by people with disabilities when entering information into an input form.

[1209] Server: Stores the determined emotion information in a database along with the user profile.

[1210] Job matching generation and notification

[1211] Server: Matches the job details table with the user profile table to perform appropriate job matching. Checks whether the task content and conditions match the user's available tasks and restrictions.

[1212] Examples:

[1213] The server compares the tasks of "plating" and "washing dishes" with job ID 1234 with the profile of user ID 5678 and calculates a matching score. At this time, it also takes into account the "sense of security" the user feels when "plating."

[1214] Server: Stores the matching results, including the matching score, in a matching table and notifies the companies and people with disabilities of the results.

[1215] Device: Company recruiters and people with disabilities can check the matching results on their respective dashboards.

[1216] Prompt Sentence Examples

[1217] Here are some examples of prompts to input to the generative AI model:

[1218] Analyze job information entered by company recruiters and break it down into appropriate tasks. Then, perform job matching and generate matching results taking into account the abilities and limitations of the disabled persons entered. Optimize the results by also taking into account the emotional information of the disabled persons.

[1219] Through these steps, the system performs detailed job matching between companies and people with disabilities, providing more suitable employment opportunities. It also takes into account the user's feelings, providing a matching process that reduces the mental burden.

[1220] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1221] Step 1: Enter job information

[1222] Terminal: The company's recruiter enters job details into the input form, including a job summary, specific job duties, and required skills and conditions.

[1223] Input: Enter job details (e.g., "Store management, stock management, staff shift management").

[1224] Specific operation: A recruiter enters job information into a form on the terminal, and the information is sent to the server.

[1225] Step 2: Job information analysis and task decomposition

[1226] Server: The server receives the job information, analyzes it using a natural language processing (NLP) algorithm, and breaks down the analysis results into multiple specific tasks.

[1227] Input: Received job information.

[1228] Data processing / calculation: Job information is analyzed using natural language processing and broken down into individual tasks.

[1229] Output: Decomposed task information (e.g., "Inventory management," "Customer support," "Sales management").

[1230] Specific operation: The server breaks down "store management, purchasing management, staff shift management" into "inventory management," "customer support," and "sales management."

[1231] Step 3: Save task information

[1232] Server: Stores the decomposed task information and its associated conditions (e.g., physical conditions and skill requirements) in a database.

[1233] Input: Decomposed task information.

[1234] Data processing / calculation: Task information and conditions are associated and saved in the database.

[1235] Output: The saved database entries.

[1236] Specific operation: Assign conditions such as "basic arithmetic ability" and "interpersonal skills" to "inventory management" and store this information in a database.

[1237] Step 4: Enter the abilities and limitations of the person with a disability

[1238] Device: People with disabilities enter the tasks they can perform and the conditions they cannot deal with into a checklist-style input form.

[1239] Input: Information about the abilities and limitations of the person with a disability (e.g., "Tasks that can be done: plating food," "Tasks that cannot be done: lifting heavy objects," "Limitations: using a wheelchair").

[1240] Specific operation: A person with a disability enters their abilities and limitations into a form on the device, and that information is sent to the server.

[1241] Step 5: Save your user profile

[1242] Server: The entered information about the abilities and limitations of the disabled person is saved in a database as a user profile.

[1243] Input: Disability ability and limitation information.

[1244] Data processing / calculation: Convert the input information into a profile format and save it in the database.

[1245] Output: The saved user profile.

[1246] Specific actions: Information on "serving food," "carrying heavy objects," and "using a wheelchair" is stored in a database.

[1247] Step 6: Emotion Recognition with the Emotion Engine

[1248] Device: An emotion engine is used to analyze the text and facial expressions of people with disabilities as they type, thereby determining their emotional state (e.g., tension, anxiety, relief, etc.) at the time of input.

[1249] Input: Input and facial expression data from the person with a disability.

[1250] Data processing / calculation: The emotion engine analyzes input content and facial expressions to determine the emotional state.

[1251] Output: Determined emotion information (e.g., "anxiety").

[1252] Specific operation: The system detects "anxiety" from the facial expressions and writing of people with disabilities.

[1253] Step 7: Storing Emotional Information

[1254] Server: Stores the determined emotion information in a database along with the user profile.

[1255] Input: Determined emotion information.

[1256] Data processing / calculation: Emotional information is added to the user profile and stored in the database.

[1257] Output: The updated user profile.

[1258] Specific behavior: Save the emotional information "anxiety" along with the profile data.

[1259] Step 8: Match job details with user profile

[1260] Server: Matches the job details table with the user profile table to perform appropriate job matching. Checks whether the task content and conditions match the user's available tasks and restrictions.

[1261] Input: Job details and user profile information.

[1262] Data processing / calculation: Compare job details with user profile and calculate compatibility.

[1263] Output: Matching results and matching score (e.g., matching score of 85 for the tasks "plating" and "washing dishes").

[1264] Specific operation: The server matches the tasks "plating" and "washing dishes" of job ID 1234 with the profile of user ID 5678 and calculates the matching score.

[1265] Step 9: Notification of Matching Results

[1266] Server: Stores the matching results, including the matching score, in a matching table and notifies the companies and people with disabilities of the results.

[1267] Input: Matching results and matching scores.

[1268] Data processing / calculation: The matching results and matching scores are stored as a set in the matching table, and a notification message is generated.

[1269] Output: Notification message (e.g., "Matching result: Job ID 1234, score 85").

[1270] Specific operation: The matching score of 85 is saved in the database and notified to the company and the person with a disability.

[1271] Step 10: Check the results

[1272] Device: Company recruiters and people with disabilities can view matching results on their dashboards.

[1273] Input: Your dashboard login details.

[1274] Output: A screen showing the matching results and matching scores.

[1275] What it does: Corporate recruiters and people with disabilities can view matched candidates and their matching scores on a dashboard.

[1276] Through these processing steps, the system performs detailed job matching between companies and people with disabilities, providing appropriate employment opportunities. It also takes into account the user's feelings, making it possible to provide a matching process that reduces the mental burden.

[1277] (Application example 2)

[1278] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1279] It is necessary to improve the work efficiency of people with disabilities working in factories while reducing their mental burden. In particular, there is a need to achieve more accurate job matching by breaking down job information into tasks that are appropriate for the abilities of people with disabilities and by taking into account their emotional state at the time. It is also important to provide an environment where people with disabilities can work in real time in an emotionally appropriate state.

[1280] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1281] In this invention, the server includes: an input means for inputting job information provided by a company; an analysis means including artificial intelligence for analyzing the input job information and breaking it down into multiple individual tasks; a storage means for saving the analyzed individual tasks and their associated conditions in a database; an input means for a user to input their own abilities and limitations; a storage means for saving the input user's ability and limitation information in the database; a matching means for collating the saved job information with user information to generate an optimal job match; a notification means for notifying the company and the user of the matching results; an emotion engine that recognizes the user's emotional state; a storage means for saving the emotion information recognized by the emotion engine in a profile; and a matching means for calculating a matching score taking the user's emotion information into consideration. This allows individuals with disabilities to be assigned tasks that are suited to their abilities and to work with less mental strain.

[1282] An "input means" is a device or method for receiving data. It typically includes a keyboard, mouse, touch screen, voice input device, etc.

[1283] "Analysis means" refers to a device or method for breaking down input data and understanding its meaning and structure. This includes artificial intelligence and natural language processing algorithms.

[1284] "Artificial intelligence" is a technology that allows computer systems to imitate human intellectual behavior and make judgments and learn.

[1285] "Storage" means a device or method for long-term storage of data. This includes databases and cloud storage.

[1286] A "database" is a structured collection of data that is systematically organized, stored, and can be efficiently searched and updated.

[1287] A "matching means" is a device or method for comparing different data to evaluate the degree of agreement or compatibility.

[1288] "Notification medium" means a device or method for communicating information to a specific person or system, including email, SMS, in-app notifications, etc.

[1289] An "emotion engine" is a device or method for analyzing and identifying a user's emotional state. It includes technologies such as facial expression recognition and voice analysis.

[1290] A "profile" is a collection of information about a particular user, including their capabilities, limitations, emotional state, etc.

[1291] A "matching score" is a numerical representation of the degree of suitability or agreement of the matching result. For example, it may include an evaluation score out of 100 points.

[1292] This invention is a system that improves the work efficiency and reduces the mental burden of disabled workers in factories. The system includes the following main components and functions:

[1293] 1. Entering and analyzing job information

[1294] Company processing

[1295] The server provides input means for company recruiters to enter job details. This input means can include a text input form or a voice input device. The entered job information is received by the server and broken down into multiple individual tasks using a natural language processing (NLP) algorithm. The analyzed individual tasks are then stored in a database.

[1296] 2. Input of the abilities and limitations of the person with a disability

[1297] Processing for people with disabilities

[1298] The device provides an input method for people with disabilities to enter their capabilities and limitations. This input method can be a checklist-style form or a touchscreen. The information entered is stored in a database as a user profile.

[1299] 3. Emotion Recognition by Emotion Engine

[1300] Emotion recognition processing

[1301] The device uses an emotion engine to analyze the text and facial expressions entered by users with disabilities. This emotion engine uses hardware such as a facial recognition camera and a voice analyzer, as well as software such as EmotionRecognizer. The emotional information that is identified is stored in a database along with the user profile.

[1302] 4. Job matching generation and notification

[1303] Matching process

[1304] The server compares the job details table with the user profile table to perform appropriate job matching. It checks whether the task content and conditions match the user's available tasks and constraints. It also calculates a matching score taking into account the user's emotional information. The calculation results are saved in the matching table and notified to the company and the person with a disability.

[1305] Specific examples

[1306] If a disabled factory worker inputs "I'll do my best today," the emotion recognition engine will detect positive emotions such as "relief." When job information such as "store management, purchasing management, and staff shift management" is given, this information is broken down into tasks such as "inventory management," "customer service," and "sales management." The broken down tasks are then compared with the user profile to match the most suitable tasks.

[1307] Prompt Sentence Examples

[1308] Job information: Store management, purchasing management, staff shift management

[1309] Emotion input: I'll do my best today too

[1310] User profile: Possible tasks: Inventory management, sales management; Impossible tasks: Customer support

[1311] This system allows people with disabilities to be assigned tasks that suit their abilities, allowing them to work with less mental strain.

[1312] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1313] Step 1:

[1314] A company's recruiter uses a terminal to input job information. Input methods include text input forms and voice input devices. Job details such as "store management, purchasing management, and staff shift management" are entered. The server receives the input job information and temporarily stores it in a database.

[1315] Input: Job information (text or audio format)

[1316] Output: Saved job information

[1317] Step 2:

[1318] The server analyzes the input job information using a natural language processing (NLP) algorithm and breaks it down into multiple individual tasks. For example, job information such as "store management, purchasing management, and staff shift management" is broken down into specific tasks such as "inventory management," "customer service," and "sales management." Each broken down task is assigned related conditions (such as required skills and physical conditions) and stored in a database.

[1319] Input: Job information

[1320] Output: Analyzed individual tasks and associated conditions

[1321] Step 3:

[1322] The terminal provides an input means for people with disabilities to enter their abilities and limitations. To do this, people with disabilities use a checklist-style form or a touch screen to enter information such as "possible task: serving food," "impossible task: carrying heavy objects," and "limitations: using a wheelchair." The entered ability and limitation information is received by the server and stored in a database as a user profile.

[1323] Input: Disability capabilities and limitations information

[1324] Output: Saved user profile

[1325] Step 4:

[1326] The device uses an emotion engine to analyze the text and facial expressions entered by the person with a disability. For example, if a person with a disability enters "I'll do my best today," the emotion engine analyzes their facial expression and tone of voice to identify positive emotions such as "relief." The recognized emotion information is then added to a profile by the server.

[1327] Input: Text and facial expression data of a person with a disability

[1328] Output: Parsed emotion information

[1329] Step 5:

[1330] The server compares the stored job information with the user profile to generate optimal job matching. Task content and conditions are matched based on the user's available tasks and constraints. Furthermore, the server also considers the user's emotional information and calculates a matching score to minimize mental strain. For example, if a particular task is mentally stressful for the user, the score for that task will be reduced.

[1331] Input: Job information, user profile, emotion information

[1332] Output: Matching score and matching result

[1333] Step 6:

[1334] The server notifies the company and the person with a disability of the matching results via email, SMS, in-app notifications, etc. The company's recruiter and the person with a disability can check the matching results on their dashboard and receive instructions for performing the appropriate tasks.

[1335] Input: Matching results

[1336] Output: Notified matching results

[1337] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1338] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1339] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1340] [Fourth embodiment]

[1341] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1342] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1343] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1344] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1345] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1346] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1347] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1348] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1349] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1350] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1351] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1352] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1353] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1354] The present invention is a system that realizes optimal job matching by analyzing job information provided by companies and breaking it down into tasks that can be performed by people with disabilities. Specific embodiments of the system are described below.

[1355] Overall system overview

[1356] The system consists of the following main functions:

[1357] 1. Entering and analyzing job information

[1358] 2. Input of the abilities and limitations of the person with a disability

[1359] 3. Job matching generation and notification

[1360] 1. Entering and analyzing job information

[1361] Company processing

[1362] Terminal: Provides a form for company recruiters to enter job details in natural language, including a job summary, specific job duties, and required skills and qualifications.

[1363] Server: Once job information is input, it uses natural language processing (NLP) algorithms and machine learning models to analyze it, which breaks it down into multiple specific tasks.

[1364] Server: Each decomposed task and its associated conditions (e.g., physical conditions and skill requirements) are stored in a database.

[1365] Examples:

[1366] When a company recruiter inputs "store management, purchasing management, and staff shift management," the AI ​​analyzes this and breaks it down into tasks such as "inventory management," "customer service," and "sales management." Each task is assigned a requirement such as "basic arithmetic ability" and "interpersonal skills."

[1367] 2. Input of the abilities and limitations of the person with a disability

[1368] Processing for people with disabilities

[1369] Device: Provides a checklist-style form for people with disabilities to enter their capabilities and limitations, including tasks they can perform and conditions they cannot accommodate.

[1370] Server: The information entered is stored in a database as a user profile.

[1371] Examples:

[1372] When a person with a disability enters "Tasks they can do: plating food," "Tasks they cannot do: carrying heavy objects," and "Restrictions: using a wheelchair," that information is saved in a database.

[1373] 3. Job matching generation and notification

[1374] Matching process

[1375] Server: Matches the job details table with the user profile table and generates matching candidates based on matching tasks and conditions.

[1376] Server: Calculates the matching score and generates the best job matching based on it. The matching score is determined by the compatibility of the task and the user's skills and constraints.

[1377] Server: Stores the matching results in a database and notifies companies and people with disabilities of the results.

[1378] Examples:

[1379] The server compares the tasks of "plating" and "washing dishes" with job ID 1234 with the profile of user ID 5678 and calculates a matching score. If the score is 85, the result is saved in the database and notified to the company and the person with a disability.

[1380] Checking the results

[1381] Device: Company recruiters and people with disabilities can view matching results on their dashboards.

[1382] On your device: The dashboard displays your matches and their matching scores.

[1383] In this way, this system analyzes companies' job information in detail and matches jobs that suit the abilities and limitations of people with disabilities, aiming to increase employment opportunities for people with disabilities and reduce turnover rates.

[1384] The processing flow will be explained below.

[1385] Step 1:

[1386] User: A company's recruiter enters job information in natural language into the automated job decomposition system's input form. This information includes a job summary, specific job duties, and required skills and conditions.

[1387] Step 2:

[1388] Server: Receives input job information and passes it to a natural language processing (NLP) algorithm, which parses the job information and breaks it down into multiple individual tasks based on templates.

[1389] Step 3:

[1390] Server: The server uses machine learning models to refine the analyzed tasks and estimate the requirements for each task (e.g., specific skills or physical abilities). This determines the requirements for each task.

[1391] Step 4:

[1392] Server: Stores the decomposed tasks and their associated condition information in the task details table for later collation and matching.

[1393] Step 5:

[1394] User: A person with a disability enters information about the tasks and limitations they can perform in the form of a checklist. The checklist lists specific tasks and limitations, and the user selects which ones they can perform.

[1395] Step 6:

[1396] Server: Receives the information entered by the person with a disability and stores it in a user profile table, including the tasks they can perform and their limitations.

[1397] Step 7:

[1398] Server: Checks the stored job details table against the user profile table to perform appropriate job matching, specifically checking whether the task content and conditions match the user's available tasks and restrictions.

[1399] Step 8:

[1400] Server: Calculates a matching score based on the compatibility between the job and the user. The matching score is determined by the degree to which each task matches the user's skills and constraints.

[1401] Step 9:

[1402] Server: Saves the matching results, including the matching score, in a matching table and notifies companies and people with disabilities of the results. The optimal matching information for each user and job is provided.

[1403] Step 10:

[1404] Users: Company recruiters view the matching results through a dedicated dashboard, which displays a list of matching candidates and each candidate's matching score.

[1405] Step 11:

[1406] Users: People with disabilities can check their matching results through a dedicated dashboard, which displays a list of jobs that have been matched to them and their matching scores.

[1407] Through these steps, detailed job matching will be carried out between companies and people with disabilities, providing more appropriate employment opportunities.

[1408] Example 1

[1409] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1410] In recent years, companies have been providing a wide variety of job information, but it is difficult for people with disabilities to find tasks that they can perform appropriately. It is also difficult for people with disabilities themselves to find jobs that suit their abilities and limitations, which reduces employment opportunities and contributes to high turnover rates. Current systems often lack sufficient analysis of job information and do not properly generate or match task lists suitable for people with disabilities. Therefore, there is a need for an effective system that allows people with disabilities to find jobs that suit them and companies to hire the right personnel.

[1411] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1412] In this invention, the server includes an input means for inputting job information provided by a company, an analysis means including artificial intelligence for analyzing the input job information and breaking it down into multiple individual tasks, a storage means for saving the analyzed individual tasks and their associated conditions in a database, an input means for a user to input their own abilities and limitations, a storage means for saving the input user ability and limitation information in the database, a comparison means for comparing the saved job information with user information to generate optimal job matching, a notification means for notifying the company and user of the comparison results, and a display means for displaying the comparison results on a dashboard. This enables detailed analysis of company job information and job matching that is appropriate for the abilities and limitations of people with disabilities.

[1413] "Company" refers to an organization that provides job information and conducts recruitment activities.

[1414] "Job information" refers to information provided by companies, such as job content, required skills, conditions, etc.

[1415] "Input means" refers to an interface through which a user inputs text and options.

[1416] The "analysis means" is a system that uses artificial intelligence to analyze input job information and break it down into multiple individual tasks.

[1417] "Artificial intelligence" is a technology that uses natural language processing and machine learning models to analyze and classify data.

[1418] "Storage means" refers to a system that stores analyzed data and input information in a database.

[1419] "User" refers to a person with a disability who uses the system.

[1420] "Ability" refers to the tasks a user can perform and the skills they possess.

[1421] "Limitations" refers to constraints such as tasks that a user cannot perform or physical conditions that the user has.

[1422] The "matching means" is a system that generates optimal job matching based on the stored job information and user information.

[1423] "Notification means" is a system for notifying companies and users of the matching results.

[1424] A "display means" is a system that visually displays information to a user through an interface such as a dashboard.

[1425] The present invention is a system that realizes optimal job matching by analyzing job information provided by companies and breaking it down into tasks that can be performed by people with disabilities. Specific embodiments of the system are described below.

[1426] System Overview

[1427] The system consists of the following main hardware and software components:

[1428] Devices: Computers, smartphones, or other devices used by company recruiters and people with disabilities to enter information.

[1429] Server: A computer system that analyzes input data and stores, collates, and notifies users. Specific examples include Apache and Nginx servers.

[1430] Database: A database system for storing analyzed job information and user profiles. Specific examples include MySQL and PostgreSQL.

[1431] Artificial intelligence models: Natural language processing (NLP) algorithms and machine learning models used to parse job information and break it down into tasks. Specific examples include Python's NLTK, SpaCy, TensorFlow, and Scikit-learn.

[1432] Specific processing flow

[1433] 1. Entering and analyzing job information

[1434] Terminal: A company's recruiter enters job details into an input form, which includes a job summary, specific job duties, and required skills and conditions.

[1435] Example: A recruiter enters "store management, purchasing management, staff shift management."

[1436] Server: Once job information is entered, it is analyzed using natural language processing (NLP) algorithms and machine learning models. As a result of the analysis, the job information is broken down into multiple specific tasks.

[1437] Example: The server breaks down job information into tasks such as "inventory management," "customer support," and "sales management."

[1438] Server: Each decomposed task and its associated conditions (e.g., physical conditions and skill requirements) are stored in a database.

[1439] 2. Input of the abilities and limitations of the person with a disability

[1440] Device: People with disabilities enter their capabilities and limitations using a checklist-style form, which lists the tasks they can perform and the conditions they cannot accommodate.

[1441] Example: A person with a disability enters "Tasks I can do: Placing food on the table," "Tasks I cannot do: Carrying heavy objects," and "Restrictions: Using a wheelchair."

[1442] Server: The entered information is stored in a database as a user profile.

[1443] 3. Job matching generation and notification

[1444] Server: Compares the job details table with the user profile table and generates matching candidates based on compatible tasks and conditions. Specifically, it uses natural language processing and machine learning models to calculate the compatibility between tasks and user profiles.

[1445] Example: The server matches the "plating" task with the user's profile and calculates a matching score.

[1446] Server: Generates optimal job matches based on the matching scores, stores the results in a database, and notifies companies and people with disabilities of the results.

[1447] 4. Check the results

[1448] Device: Corporate recruiters and people with disabilities can check their matching results on their own dashboard.

[1449] Example: Companies and people with disabilities evaluate the matching results confirmed through the dashboard and take the following actions:

[1450] Prompt Sentence Examples

[1451] Analyze job information entered by companies, break it down into specific tasks, and compare it with the abilities and limitations entered by individuals with disabilities to generate an appropriate job matching score.

[1452] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1453] Step 1:

[1454] The terminal provides an input form for company recruiters to enter job details. The recruiter inputs the job summary, specific work content, required skills and conditions in natural language. This input sends the job information to the server. Input data includes "store management, purchasing management, staff shift management," etc.

[1455] Step 2:

[1456] The server stores the received job information in a temporary database, which is used for later analysis. The stored data is the entire job information entered.

[1457] Step 3:

[1458] The server begins to analyze the stored job information. Using natural language processing (NLP) algorithms (such as Python's NLTK or SpaCy) and machine learning models (such as TensorFlow or Scikit-learn), it analyzes the job information and breaks it down into multiple specific tasks. The input data is the entire job information, and the output data is the broken down task list and corresponding conditions. For example, the job information is broken down into the tasks "inventory management," "customer support," and "sales management."

[1459] Step 4:

[1460] The server stores each decomposed task and its associated conditions in a database. The stored data includes detailed information about each task (e.g., "basic arithmetic ability" for "inventory management" and "interpersonal skills" for "customer service").

[1461] Step 5:

[1462] The device provides a checklist-style input form for people with disabilities to enter their abilities and limitations. People with disabilities enter the tasks they can do and the conditions they cannot handle. This input creates a user profile, which is sent to the server. Input data includes such things as "Tasks they can do: plating food," "Tasks they cannot do: carrying heavy objects," and "Limitations: using a wheelchair."

[1463] Step 6:

[1464] The server stores the data received from the disabled person in a temporary database, which is later used for matching purposes. The stored data is the entire entered user profile.

[1465] Step 7:

[1466] The server compares the saved job information with the user profile and generates matching candidates based on compatible tasks and conditions. This uses natural language processing and machine learning models, with the input data being the job details table and user profile table, and the output data being the matching candidates. The server calculates the compatibility between the task and the user's skills and restrictions, and calculates a matching score. As a specific example, the task "plating" is compared with the user's profile, and the matching score is calculated as 75 points.

[1467] Step 8:

[1468] The server stores the matching results in a database and notifies the company and the person with a disability of the results. The stored data is the matching score and the corresponding task list, and the notification includes the job ID, user ID, and compatibility score.

[1469] Step 9:

[1470] The device provides an interface for corporate recruiters and people with disabilities to check matching results on their own dashboards. The data displayed is the matched candidates and their matching scores. For example, the dashboard might show that "User ID 5678 matches Job ID 1234 with a matching score of 75."

[1471] (Application example 1)

[1472] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1473] Previously, there were systems that analyzed job information provided by companies and matched them with tasks suitable for people with disabilities, but these systems did not support real-time task notifications or execution support, making it difficult for people with disabilities to continuously perform appropriate tasks at work sites such as logistics centers.In addition, people with disabilities could not easily recognize or understand the optimal tasks according to their own situation, making it difficult to increase employment opportunities and achieve efficient work.

[1474] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1475] In this invention, the server includes: an input means for inputting job information provided by a company; an analysis means including artificial intelligence for analyzing the input job information and breaking it down into multiple individual tasks; a storage means for saving the analyzed individual tasks and their associated conditions in a database; an input means for a user to input their own abilities and limitations; a storage means for saving the input user ability and limitation information in the database; a matching means for collating the saved job information and user information to generate optimal job matching; a notification means for notifying the company and the user of the matching results; and a head-mounted display including a display device for displaying the notified tasks in real time and supporting their completion. This enables people with disabilities at logistics centers to recognize and appropriately complete the tasks that are optimal for them in real time.

[1476] An "enterprise" is an organization that conducts business, such as a company or corporation.

[1477] "Job information" refers to information provided by a company, such as the business content, job details, required skills and conditions, etc.

[1478] "Input means" means a device or software for inputting information into a system.

[1479] "Analysis means" refers to a device or software that breaks down input information and extracts meaning.

[1480] "Artificial intelligence" is a technology that uses machine learning and natural language processing to analyze data and solve problems.

[1481] "Storage means" refers to a device or software for storing data for a certain period of time.

[1482] A "database" is a system for efficiently storing, managing, and searching data.

[1483] "User" refers to any person, including a person with a disability, who uses the system and receives tasks.

[1484] "Ability" refers to the skills and tasks that a user can perform.

[1485] "Limitations" refer to skills or tasks that a user cannot perform.

[1486] The "matching means" refers to a device or software that compares the stored job information with the user information and derives the optimal match.

[1487] "Notification means" means a device or software for notifying users of match results or other information.

[1488] A "head-mounted display" is a device worn on the head to display information.

[1489] "Real-time" refers to processing and information exchange occurring instantly with little or no delay.

[1490] Overall system overview

[1491] This invention is a system for efficiently matching tasks for people with disabilities in logistics centers. The system inputs and analyzes job information, inputs the abilities and limitations of people with disabilities, generates and notifies job matching, and provides real-time task notification and execution support.

[1492] 1. Entering and analyzing job information

[1493] The company's terminal has an input means for entering job information. The entered job information is analyzed by the server. Natural language processing (NLP) and machine learning models are used for the analysis. This breaks down the job information into multiple individual tasks. The analyzed tasks and their associated conditions are stored in a database by the server.

[1494] For example, if a company recruiter inputs "stock organization, packing, and product movement," the AI ​​will break this down into "inventory management," "packing work," and "transportation work." Each task will be assigned a condition such as "basic arithmetic ability" or "manual dexterity."

[1495] 2. Input of the abilities and limitations of the person with a disability

[1496] The device on the disabled person's side has a checklist-style input means for entering their abilities and limitations. The input information is saved in a database as a user profile, which clarifies the tasks that the disabled person can perform and their limitations.

[1497] For example, if a person with a disability enters "Tasks they can do: picking," "Tasks they cannot do: working at heights," and "Limitations: using a wheelchair," that information is saved in the database.

[1498] 3. Job matching generation and notification

[1499] The server uses a matching method to match job information with user profiles and generate optimal job matches. The matching score is determined by the compatibility of the task with the user's skills and limitations. The matching results are stored in a database by the server and notified to companies and people with disabilities.

[1500] As a concrete example, the server compares the "picking" and "packing" tasks with job ID 1234 with the profile of user ID 5678 and calculates a matching score. If the score is 85, the result is saved in the database and notified to the company and the person with a disability.

[1501] 4. Real-time task notifications and assistance

[1502] The matching results are notified to the person with a disability in real time via a head-mounted display (e.g., HMD). The HMD displays the notified tasks in real time and provides instructions to assist in their completion. This streamlines task management within the logistics center and enables people with disabilities to perform tasks optimally.

[1503] As a concrete example, a person with a disability can be notified in real time, "Your next task is picking. Please take the product from the designated shelf," and can then follow the instructions to carry out the task.

[1504] Prompt Sentence Examples

[1505] Here are some examples of prompts to input to a generative AI model:

[1506] text

[1507] Consider a detailed design proposal for a system that matches the abilities of people with disabilities with job information. The system uses natural language processing to analyze job information and break it down into specific tasks. It also inputs each user's profile and matches it with job information to suggest the most suitable job.

[1508] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1509] Step 1:

[1510] Entering job information

[1511] How it works: A company recruiter enters job information in natural language on a terminal.

[1512] Input: Job summary, specific job duties, required skills and conditions.

[1513] Output: Raw job information sent to the server.

[1514] Specific operation: The company enters the job details as "Pick, pack, and move goods."

[1515] Step 2:

[1516] Job Information Analysis

[1517] How it works: The server analyzes the input job information using natural language processing (NLP) and breaks it down into multiple individual tasks.

[1518] Input: Unparsed job information.

[1519] Output: Analyzed individual tasks and associated conditions stored in a database.

[1520] Specific operation: The server breaks down the "picking and packing" job into "inventory management," "packing work," and "transportation work," and assigns conditions such as "basic arithmetic ability" and "manual dexterity" to each.

[1521] Step 3:

[1522] Entering user capabilities and limitations

[1523] How it works: A person with a disability enters their abilities and limitations in a checklist format on a terminal.

[1524] Input: Tasks that can be performed and conditions that cannot be met.

[1525] Output: Profile information of disabled people stored in a database.

[1526] Specific actions: A person with a disability enters "Tasks they can do: picking items," "Tasks they cannot do: working at heights," and "Restrictions: using a wheelchair."

[1527] Step 4:

[1528] Job Matching Generation

[1529] Operation: The server compares the stored job information with the user's capabilities and restrictions to generate the optimal job matching.

[1530] Input: Parsed job information, user profile.

[1531] Output: Matching results and matching scores.

[1532] Specific operation: The server matches the "picking" and "packing" of job ID 1234 with the profile of user ID 5678 and calculates a matching score of 85.

[1533] Step 5:

[1534] Generate and send notifications

[1535] Operation: The server stores the matching results in a database and notifies the company and the person with a disability.

[1536] Input: Job matching results.

[1537] Output: Notifications displayed on corporate and disability devices.

[1538] Specific action: The server sends a notification saying "User ID 5678 matches job ID 1234."

[1539] Step 6:

[1540] Real-time notifications and assistance

[1541] How it works: A person with a disability wears a head-mounted display (HMD) and performs tasks displayed in real time.

[1542] Input: Real-time task notifications from the server.

[1543] Output: Task instructions displayed during execution.

[1544] Specific actions: A person with a disability puts on the HMD and follows the instructions displayed, such as, "The next task is picking. Please take the product from the designated shelf."

[1545] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1546] The present invention is a system that not only analyzes job information provided by companies and breaks it down into tasks that can be performed by people with disabilities, but also combines it with an emotion engine that recognizes the emotions of users, thereby achieving more accurate job matching. Specific embodiments of the system are described below.

[1547] Overall system overview

[1548] The system consists of the following main functions:

[1549] 1. Entering and analyzing job information

[1550] 2. Input of the abilities and limitations of the person with a disability

[1551] 3. Emotion Recognition by Emotion Engine

[1552] 4. Job matching generation and notification

[1553] 1. Entering and analyzing job information

[1554] Company processing

[1555] Terminal: Provides a form for company recruiters to enter job details in natural language, including a job summary, specific job duties, and required skills and qualifications.

[1556] Server: Once job information is input, it uses natural language processing (NLP) algorithms and machine learning models to analyze it, which breaks it down into multiple specific tasks.

[1557] Server: Each decomposed task and its associated conditions (e.g., physical conditions and skill requirements) are stored in a database.

[1558] Examples:

[1559] When a company recruiter inputs "store management, purchasing management, and staff shift management," the AI ​​analyzes this and breaks it down into tasks such as "inventory management," "customer service," and "sales management." Each task is assigned a requirement such as "basic arithmetic ability" and "interpersonal skills."

[1560] 2. Input of the abilities and limitations of the person with a disability

[1561] Processing for people with disabilities

[1562] Device: Provides a checklist-style form for people with disabilities to enter their capabilities and limitations, including tasks they can perform and conditions they cannot accommodate.

[1563] Server: The information entered is stored in a database as a user profile.

[1564] Examples:

[1565] When a person with a disability enters "Tasks they can do: plating food," "Tasks they cannot do: carrying heavy objects," and "Restrictions: using a wheelchair," that information is saved in a database.

[1566] 3. Emotion Recognition by Emotion Engine

[1567] Emotion recognition processing

[1568] Device: An emotion engine is used to analyze the text and facial expressions of people with disabilities as they type, thereby determining their emotional state (e.g., tension, anxiety, relief, etc.) at the time of input.

[1569] Server: The determined emotional information is stored in a database along with the disabled person's profile.

[1570] Examples:

[1571] If a person with a disability feels "a little anxious" when filling out a form, that emotional information will also be saved.

[1572] 4. Job matching generation and notification

[1573] Matching process

[1574] Server: Checks the job details table against the user profile table to perform appropriate job matching. Specifically, it checks whether the task content and conditions match the user's available tasks and restrictions.

[1575] Server: The server also takes into account the user's emotional information and reflects it in the calculation of the matching score. For example, if a particular task is mentally demanding for the user, this will also affect the matching score.

[1576] Server: Saves the matching results, including the matching score, in a matching table and notifies companies and people with disabilities of the results. The optimal matching information for each user and job is provided.

[1577] Examples:

[1578] The server compares the tasks of "plating" and "washing dishes" with job ID 1234 with the profile of user ID 5678 and calculates a matching score. The server also takes into account the "sense of security" the user feels when "plating." If the score is 85, the result is saved in the database and notified to the company and the person with a disability.

[1579] Checking the results

[1580] Device: Company recruiters and people with disabilities can view matching results on their dashboards.

[1581] On your device: The dashboard displays your matches and their matching scores.

[1582] Through these steps, detailed job matching between companies and people with disabilities is carried out, providing more suitable employment opportunities. The system also takes into account the emotions of users, providing a matching process that reduces the mental burden.

[1583] The processing flow will be explained below.

[1584] Step 1:

[1585] User: A company's recruiter enters job information in natural language into the automated job decomposition system's input form. This information includes a job summary, specific job duties, and required skills and conditions.

[1586] Step 2:

[1587] Server: Receives input job information and passes it to a natural language processing (NLP) algorithm, which parses the job information and breaks it down into multiple individual tasks based on templates.

[1588] Step 3:

[1589] Server: The server uses machine learning models to refine the analyzed tasks and estimate the requirements for each task (e.g., specific skills or physical abilities). This determines the requirements for each task.

[1590] Step 4:

[1591] Server: Stores the decomposed tasks and their associated condition information in the task details table for later collation and matching.

[1592] Step 5:

[1593] User: A person with a disability enters information about the tasks and limitations they can perform in the form of a checklist. The checklist lists specific tasks and limitations, and the user selects which ones they can perform.

[1594] Step 6:

[1595] Device: When a person with a disability uses an input form, an emotion engine runs in the background, analyzing facial expressions and text in real time as they enter information.

[1596] Step 7:

[1597] Server: Receives the emotional data analyzed by the emotion engine, associates it with the user profile, and stores it in a database, along with the emotional state at the time of input.

[1598] Step 8:

[1599] Server: Receives task and emotion information entered by users with disabilities and stores it in a user profile table. The stored information includes tasks that can be performed, limitations, and emotion data at the time of input.

[1600] Step 9:

[1601] Server: Checks the job details table against the user profile table to perform appropriate job matching, specifically checking whether the task content and conditions match the user's available tasks and restrictions.

[1602] Step 10:

[1603] Server: The server also takes into account the user's emotional information and reflects it in the calculation of the matching score. For example, if a particular task is mentally demanding for the user, this will also affect the matching score.

[1604] Step 11:

[1605] Server: Saves the matching results, including the matching score, in a matching table and notifies companies and people with disabilities of the results. The optimal matching information for each user and job is provided.

[1606] Step 12:

[1607] Users: Company recruiters view the matching results through a dedicated dashboard, which displays a list of matching candidates and each candidate's matching score.

[1608] Step 13:

[1609] Users: People with disabilities can check their matching results through a dedicated dashboard, which displays a list of jobs that have been matched to them and their matching scores.

[1610] Through these steps, detailed job matching between companies and people with disabilities is carried out, providing more suitable employment opportunities. The system also takes into account the emotions of users, providing a matching process that reduces the mental burden.

[1611] Example 2

[1612] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1613] Conventional job matching systems only consider the user's abilities and limitations, but do not consider their emotional state, which means they are unable to match people in a way that reduces their mental burden. Furthermore, they are unable to properly analyze job information and break it down into individual tasks, which can result in poor job compatibility.

[1614] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for inputting job information provided by a company, an analysis means including artificial intelligence for analyzing the input job information and breaking it down into multiple individual tasks, a storage means for saving the analyzed individual tasks and their associated conditions in a database, an input means for a user to input their own abilities and limitations, a storage means for saving the input user ability and limitation information in the database, an analysis means for analyzing the user's emotional state using an emotion engine, a storage means for saving the saved user emotion information in the database, a matching means for collating the saved job information and user information to generate an optimal job match, and a notification means for notifying the company and the user of the matching result. This enables job matching that comprehensively takes into account the user's abilities, limitations, and emotional state, thereby achieving appropriate matching with reduced mental burden.

[1615] "Job information" is information that includes an overview of the work provided by a company, specific work content, and required skills and conditions.

[1616] An "input means" is a device or program that provides an interface for companies or users to input information into the system.

[1617] An "analysis means" is a device or program that includes artificial intelligence or natural language processing algorithms to process input information and break it down into multiple individual tasks.

[1618] The "storage means" is a device or program for storing analyzed information and input information in a database.

[1619] "User" means a person with a disability or their representative who uses the system to input their capabilities and limitations.

[1620] An "emotion engine" is a device or program that analyzes a user's input and facial expressions to determine their emotional state.

[1621] The "matching means" is a device or program for matching the stored job information with the user information and emotion information to generate optimal job matching.

[1622] The "notification means" is a device or program for notifying companies and users of the generated matching results.

[1623] The "matching score" is a numerical representation of the degree of compatibility between job information and user information.

[1624] The present invention is a system that not only analyzes job information provided by companies and breaks it down into tasks that can be performed by people with disabilities, but also combines it with an emotion engine that recognizes the emotions of users, thereby achieving more accurate job matching. Specific embodiments of the system are described below.

[1625] Overall system overview

[1626] The system consists of the following main functions:

[1627] 1. Entering and analyzing job information

[1628] 2. Input of the abilities and limitations of the person with a disability

[1629] 3. Emotion Recognition by Emotion Engine

[1630] 4. Job matching generation and notification

[1631] Entering and parsing job information

[1632] Terminal: A company's recruiter fills in the job details using an input form, which includes a job summary, specific job duties, and required skills and qualifications.

[1633] Examples:

[1634] A company's recruiter would enter "store management, purchasing management, staff shift management."

[1635] Server: Receives the input job information and analyzes it using a natural language processing (NLP) algorithm. Through analysis, the job information is broken down into multiple specific tasks.

[1636] Examples:

[1637] The server receives the "store management, purchasing management, staff shift management" and breaks it down into tasks such as "inventory management," "customer support," and "sales management."

[1638] Server: The decomposed tasks and their associated conditions (e.g., physical conditions and skill requirements) are stored in a database.

[1639] Input of abilities and limitations of people with disabilities

[1640] Device: People with disabilities enter the tasks they can perform and the conditions they cannot deal with into a checklist-style input form.

[1641] Examples:

[1642] A person with a disability would enter "Tasks they can do: plating," "Tasks they cannot do: carrying heavy objects," and "Limitations: using a wheelchair."

[1643] Server: Saves the entered information as a user profile in a database.

[1644] Emotion recognition by emotion engine

[1645] Terminal: Using an emotion engine, the text and facial expressions entered by the person with a disability are analyzed to determine their emotional state at the time of input (e.g., tension, anxiety, relief, etc.).

[1646] Examples:

[1647] Detects the emotional state of "slight anxiety" felt by people with disabilities when entering information into an input form.

[1648] Server: Stores the determined emotion information in a database along with the user profile.

[1649] Job matching generation and notification

[1650] Server: Matches the job details table with the user profile table to perform appropriate job matching. Checks whether the task content and conditions match the user's available tasks and restrictions.

[1651] Examples:

[1652] The server compares the tasks of "plating" and "washing dishes" with job ID 1234 with the profile of user ID 5678 and calculates a matching score. At this time, it also takes into account the "sense of security" the user feels when "plating."

[1653] Server: Stores the matching results, including the matching score, in a matching table and notifies the companies and people with disabilities of the results.

[1654] Device: Company recruiters and people with disabilities can check the matching results on their respective dashboards.

[1655] Prompt Sentence Examples

[1656] Here are some examples of prompts to input to the generative AI model:

[1657] Analyze job information entered by company recruiters and break it down into appropriate tasks. Then, perform job matching and generate matching results taking into account the abilities and limitations of the disabled persons entered. Optimize the results by also taking into account the emotional information of the disabled persons.

[1658] Through these steps, the system performs detailed job matching between companies and people with disabilities, providing more suitable employment opportunities. It also takes into account the user's feelings, providing a matching process that reduces the mental burden.

[1659] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1660] Step 1: Enter job information

[1661] Terminal: The company's recruiter enters job details into the input form, including a job summary, specific job duties, and required skills and conditions.

[1662] Input: Enter job details (e.g., "Store management, stock management, staff shift management").

[1663] Specific operation: A recruiter enters job information into a form on the terminal, and the information is sent to the server.

[1664] Step 2: Job information analysis and task decomposition

[1665] Server: The server receives the job information, analyzes it using a natural language processing (NLP) algorithm, and breaks down the analysis results into multiple specific tasks.

[1666] Input: Received job information.

[1667] Data processing / calculation: Job information is analyzed using natural language processing and broken down into individual tasks.

[1668] Output: Decomposed task information (e.g., "Inventory management," "Customer support," "Sales management").

[1669] Specific operation: The server breaks down "store management, purchasing management, staff shift management" into "inventory management," "customer support," and "sales management."

[1670] Step 3: Save task information

[1671] Server: Stores the decomposed task information and its associated conditions (e.g., physical conditions and skill requirements) in a database.

[1672] Input: Decomposed task information.

[1673] Data processing / calculation: Task information and conditions are associated and saved in the database.

[1674] Output: The saved database entries.

[1675] Specific operation: Assign conditions such as "basic arithmetic ability" and "interpersonal skills" to "inventory management" and store this information in a database.

[1676] Step 4: Enter the abilities and limitations of the person with a disability

[1677] Device: People with disabilities enter the tasks they can perform and the conditions they cannot deal with into a checklist-style input form.

[1678] Input: Information about the abilities and limitations of the person with a disability (e.g., "Tasks that can be done: plating food," "Tasks that cannot be done: lifting heavy objects," "Limitations: using a wheelchair").

[1679] Specific operation: A person with a disability enters their abilities and limitations into a form on the device, and that information is sent to the server.

[1680] Step 5: Save your user profile

[1681] Server: The entered information about the abilities and limitations of the disabled person is saved in a database as a user profile.

[1682] Input: Disability ability and limitation information.

[1683] Data processing / calculation: Convert the input information into a profile format and save it in the database.

[1684] Output: The saved user profile.

[1685] Specific actions: Information on "serving food," "carrying heavy objects," and "using a wheelchair" is stored in a database.

[1686] Step 6: Emotion Recognition with the Emotion Engine

[1687] Device: An emotion engine is used to analyze the text and facial expressions of people with disabilities as they type, thereby determining their emotional state (e.g., tension, anxiety, relief, etc.) at the time of input.

[1688] Input: Input and facial expression data from the person with a disability.

[1689] Data processing / calculation: The emotion engine analyzes input content and facial expressions to determine the emotional state.

[1690] Output: Determined emotion information (e.g., "anxiety").

[1691] Specific operation: The system detects "anxiety" from the facial expressions and writing of people with disabilities.

[1692] Step 7: Storing Emotional Information

[1693] Server: Stores the determined emotion information in a database along with the user profile.

[1694] Input: Determined emotion information.

[1695] Data processing / calculation: Emotional information is added to the user profile and stored in the database.

[1696] Output: The updated user profile.

[1697] Specific behavior: Save the emotional information "anxiety" along with the profile data.

[1698] Step 8: Match job details with user profile

[1699] Server: Matches the job details table with the user profile table to perform appropriate job matching. Checks whether the task content and conditions match the user's available tasks and restrictions.

[1700] Input: Job details and user profile information.

[1701] Data processing / calculation: Compare job details with user profile and calculate compatibility.

[1702] Output: Matching results and matching score (e.g., matching score of 85 for the tasks "plating" and "washing dishes").

[1703] Specific operation: The server matches the tasks "plating" and "washing dishes" of job ID 1234 with the profile of user ID 5678 and calculates the matching score.

[1704] Step 9: Notification of Matching Results

[1705] Server: Stores the matching results, including the matching score, in a matching table and notifies the companies and people with disabilities of the results.

[1706] Input: Matching results and matching scores.

[1707] Data processing / calculation: The matching results and matching scores are stored as a set in the matching table, and a notification message is generated.

[1708] Output: Notification message (e.g., "Matching result: Job ID 1234, score 85").

[1709] Specific operation: The matching score of 85 is saved in the database and notified to the company and the person with a disability.

[1710] Step 10: Check the results

[1711] Device: Company recruiters and people with disabilities can view matching results on their dashboards.

[1712] Input: Your dashboard login details.

[1713] Output: A screen showing the matching results and matching scores.

[1714] What it does: Corporate recruiters and people with disabilities can view matched candidates and their matching scores on a dashboard.

[1715] Through these processing steps, the system performs detailed job matching between companies and people with disabilities, providing appropriate employment opportunities. It also takes into account the user's feelings, making it possible to provide a matching process that reduces the mental burden.

[1716] (Application example 2)

[1717] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1718] It is necessary to improve the work efficiency of people with disabilities working in factories while reducing their mental burden. In particular, there is a need to achieve more accurate job matching by breaking down job information into tasks that are appropriate for the abilities of people with disabilities and by taking into account their emotional state at the time. It is also important to provide an environment where people with disabilities can work in real time in an emotionally appropriate state.

[1719] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1720] In this invention, the server includes: an input means for inputting job information provided by a company; an analysis means including artificial intelligence for analyzing the input job information and breaking it down into multiple individual tasks; a storage means for saving the analyzed individual tasks and their associated conditions in a database; an input means for a user to input their own abilities and limitations; a storage means for saving the input user's ability and limitation information in the database; a matching means for collating the saved job information with user information to generate an optimal job match; a notification means for notifying the company and the user of the matching results; an emotion engine that recognizes the user's emotional state; a storage means for saving the emotion information recognized by the emotion engine in a profile; and a matching means for calculating a matching score taking the user's emotion information into consideration. This allows individuals with disabilities to be assigned tasks that are suited to their abilities and to work with less mental strain.

[1721] An "input means" is a device or method for receiving data. It typically includes a keyboard, mouse, touch screen, voice input device, etc.

[1722] "Analysis means" refers to a device or method for breaking down input data and understanding its meaning and structure. This includes artificial intelligence and natural language processing algorithms.

[1723] "Artificial intelligence" is a technology that allows computer systems to imitate human intellectual behavior and make judgments and learn.

[1724] "Storage" means a device or method for long-term storage of data. This includes databases and cloud storage.

[1725] A "database" is a structured collection of data that is systematically organized, stored, and can be efficiently searched and updated.

[1726] A "matching means" is a device or method for comparing different data to evaluate the degree of agreement or compatibility.

[1727] "Notification medium" means a device or method for communicating information to a specific person or system, including email, SMS, in-app notifications, etc.

[1728] An "emotion engine" is a device or method for analyzing and identifying a user's emotional state. It includes technologies such as facial expression recognition and voice analysis.

[1729] A "profile" is a collection of information about a particular user, including their capabilities, limitations, emotional state, etc.

[1730] A "matching score" is a numerical representation of the degree of suitability or agreement of the matching result. For example, it may include an evaluation score out of 100 points.

[1731] This invention is a system that improves the work efficiency and reduces the mental burden of disabled workers in factories. The system includes the following main components and functions:

[1732] 1. Entering and analyzing job information

[1733] Company processing

[1734] The server provides input means for company recruiters to enter job details. This input means can include a text input form or a voice input device. The entered job information is received by the server and broken down into multiple individual tasks using a natural language processing (NLP) algorithm. The analyzed individual tasks are then stored in a database.

[1735] 2. Input of the abilities and limitations of the person with a disability

[1736] Processing for people with disabilities

[1737] The device provides an input method for people with disabilities to enter their capabilities and limitations. This input method can be a checklist-style form or a touchscreen. The information entered is stored in a database as a user profile.

[1738] 3. Emotion Recognition by Emotion Engine

[1739] Emotion recognition processing

[1740] The device uses an emotion engine to analyze the text and facial expressions entered by users with disabilities. This emotion engine uses hardware such as a facial recognition camera and a voice analyzer, as well as software such as EmotionRecognizer. The emotional information that is identified is stored in a database along with the user profile.

[1741] 4. Job matching generation and notification

[1742] Matching process

[1743] The server compares the job details table with the user profile table to perform appropriate job matching. It checks whether the task content and conditions match the user's available tasks and constraints. It also calculates a matching score taking into account the user's emotional information. The calculation results are saved in the matching table and notified to the company and the person with a disability.

[1744] Specific examples

[1745] If a disabled factory worker inputs "I'll do my best today," the emotion recognition engine will detect positive emotions such as "relief." When job information such as "store management, purchasing management, and staff shift management" is given, this information is broken down into tasks such as "inventory management," "customer service," and "sales management." The broken down tasks are then compared with the user profile to match the most suitable tasks.

[1746] Prompt Sentence Examples

[1747] Job information: Store management, purchasing management, staff shift management

[1748] Emotion input: I'll do my best today too

[1749] User profile: Possible tasks: Inventory management, sales management; Impossible tasks: Customer support

[1750] This system allows people with disabilities to be assigned tasks that suit their abilities, allowing them to work with less mental strain.

[1751] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1752] Step 1:

[1753] A company's recruiter uses a terminal to input job information. Input methods include text input forms and voice input devices. Job details such as "store management, purchasing management, and staff shift management" are entered. The server receives the input job information and temporarily stores it in a database.

[1754] Input: Job information (text or audio format)

[1755] Output: Saved job information

[1756] Step 2:

[1757] The server analyzes the input job information using a natural language processing (NLP) algorithm and breaks it down into multiple individual tasks. For example, job information such as "store management, purchasing management, and staff shift management" is broken down into specific tasks such as "inventory management," "customer service," and "sales management." Each broken down task is assigned related conditions (such as required skills and physical conditions) and stored in a database.

[1758] Input: Job information

[1759] Output: Analyzed individual tasks and associated conditions

[1760] Step 3:

[1761] The terminal provides an input means for people with disabilities to enter their abilities and limitations. To do this, people with disabilities use a checklist-style form or a touch screen to enter information such as "possible task: serving food," "impossible task: carrying heavy objects," and "limitations: using a wheelchair." The entered ability and limitation information is received by the server and stored in a database as a user profile.

[1762] Input: Disability capabilities and limitations information

[1763] Output: Saved user profile

[1764] Step 4:

[1765] The device uses an emotion engine to analyze the text and facial expressions entered by the person with a disability. For example, if a person with a disability enters "I'll do my best today," the emotion engine analyzes their facial expression and tone of voice to identify positive emotions such as "relief." The recognized emotion information is then added to a profile by the server.

[1766] Input: Text and facial expression data of a person with a disability

[1767] Output: Parsed emotion information

[1768] Step 5:

[1769] The server compares the stored job information with the user profile to generate optimal job matching. Task content and conditions are matched based on the user's available tasks and constraints. Furthermore, the server also considers the user's emotional information and calculates a matching score to minimize mental strain. For example, if a particular task is mentally stressful for the user, the score for that task will be reduced.

[1770] Input: Job information, user profile, emotion information

[1771] Output: Matching score and matching result

[1772] Step 6:

[1773] The server notifies the company and the person with a disability of the matching results via email, SMS, in-app notifications, etc. The company's recruiter and the person with a disability can check the matching results on their dashboard and receive instructions for performing the appropriate tasks.

[1774] Input: Matching results

[1775] Output: Notified matching results

[1776] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1777] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1778] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1779] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1780] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1781] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1782] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1783] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1784] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1785] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1786] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1787] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1788] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1789] 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.

[1790] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1791] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1792] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1793] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1794] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1795] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1796] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1797] The following is further disclosed regarding the above embodiment.

[1798] (Claim 1)

[1799] an input means for inputting job information provided by a company;

[1800] an analysis means including artificial intelligence for analyzing input job information and breaking it down into a plurality of individual tasks;

[1801] storage means for storing the analyzed individual tasks and their associated conditions in a database;

[1802] input means for a user to input his or her capabilities and limitations;

[1803] a storage means for storing the entered user capability and restriction information in a database;

[1804] a matching means for matching the stored job information and user information to generate an optimal job match;

[1805] A system that includes a notification means for notifying companies and users of the matching results.

[1806] (Claim 2)

[1807] 2. The system according to claim 1, wherein the analyzing means analyzes the job information using natural language processing and breaks it down into individual tasks.

[1808] (Claim 3)

[1809] 2. The system according to claim 1, wherein the matching means calculates a matching score based on the suitability of different tasks and conditions to generate a matching result.

[1810] "Example 1"

[1811] (Claim 1)

[1812] an input means for inputting job information provided by a company;

[1813] an analysis means including artificial intelligence for analyzing input job information and breaking it down into a plurality of individual tasks;

[1814] storage means for storing the analyzed individual tasks and their associated conditions in a database;

[1815] input means for a user to input his or her capabilities and limitations;

[1816] a storage means for storing the entered user capability and restriction information in a database;

[1817] a matching means for matching the stored job information and user information to generate an optimal job match;

[1818] A notification method for notifying companies and users of the matching results;

[1819] The system includes a display means for displaying the reconciliation results on a dashboard.

[1820] (Claim 2)

[1821] 2. The system according to claim 1, wherein the analysis means analyzes job information using natural language processing and machine learning models and breaks it down into individual tasks.

[1822] (Claim 3)

[1823] 2. The system according to claim 1, wherein the matching means calculates a matching score based on the suitability of different tasks and conditions, generates a matching result, and stores the result in a database.

[1824] "Application Example 1"

[1825] (Claim 1)

[1826] an input means for inputting job information provided by a company;

[1827] an analysis means including artificial intelligence for analyzing input job information and breaking it down into a plurality of individual tasks;

[1828] storage means for storing the analyzed individual tasks and their associated conditions in a database;

[1829] input means for a user to input his or her capabilities and limitations;

[1830] a storage means for storing the entered user capability and restriction information in a database;

[1831] a matching means for matching the stored job information and user information to generate an optimal job match;

[1832] A notification method for notifying companies and users of the matching results;

[1833] a means for having a head-mounted display including a display device for displaying the notified task in real time and assisting in its execution;

[1834] A system including:

[1835] (Claim 2)

[1836] 2. The system according to claim 1, wherein the analyzing means analyzes the job information using natural language processing and breaks it down into individual tasks.

[1837] (Claim 3)

[1838] 2. The system according to claim 1, wherein the matching means calculates a matching score based on the suitability of different tasks and conditions to generate a matching result.

[1839] "Example 2: Combining Emotion Engines"

[1840] (Claim 1)

[1841] an input means for inputting job information provided by a company;

[1842] an analysis means including artificial intelligence for analyzing input job information and breaking it down into a plurality of individual tasks;

[1843] storage means for storing the analyzed individual tasks and their associated conditions in a database;

[1844] input means for a user to input his or her capabilities and limitations;

[1845] a storage means for storing the entered user capability and restriction information in a database;

[1846] analysis means for analyzing the emotional state of a user using an emotion engine;

[1847] a storage means for storing the stored user emotion information in a database;

[1848] a matching means for matching the stored job information and user information to generate an optimal job match;

[1849] A system that includes a notification means for notifying companies and users of the matching results.

[1850] (Claim 2)

[1851] 2. The system according to claim 1, wherein the analyzing means analyzes the job information using natural language processing and breaks it down into individual tasks.

[1852] (Claim 3)

[1853] The system according to claim 1, wherein the matching means calculates a matching score based on the suitability of different tasks and conditions, and generates a matching result taking into account emotional information of the user.

[1854] "Application example 2 when combining emotion engines"

[1855] (Claim 1)

[1856] an input means for inputting job information provided by a company;

[1857] an analysis means including artificial intelligence for analyzing input job information and breaking it down into a plurality of individual tasks;

[1858] storage means for storing the analyzed individual tasks and their associated conditions in a database;

[1859] input means for a user to input his or her capabilities and limitations;

[1860] a storage means for storing the entered user capability and restriction information in a database;

[1861] a matching means for matching the stored job information and user information to generate an optimal job match;

[1862] A notification method for notifying companies and users of the matching results;

[1863] an emotion engine that recognizes the user's emotional state;

[1864] storage means for storing the emotion information recognized by the emotion engine in a profile;

[1865] The system includes a matching means for calculating a matching score taking into account the user's emotional information.

[1866] (Claim 2)

[1867] 2. The system according to claim 1, wherein the analyzing means analyzes the job information using natural language processing and breaks it down into individual tasks.

[1868] (Claim 3)

[1869] 2. The system according to claim 1, wherein the matching means calculates a matching score based on the suitability of different tasks and conditions and the user's emotional information, and generates a matching result. [Explanation of symbols]

[1870] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. an input means for inputting job information provided by a company; an analysis means including artificial intelligence for analyzing input job information and breaking it down into a plurality of individual tasks; storage means for storing the analyzed individual tasks and their associated conditions in a database; input means for a user to input his or her capabilities and limitations; a storage means for storing the entered user capability and restriction information in a database; a matching means for matching the stored job information and user information to generate an optimal job match; A system that includes a notification means for notifying companies and users of the matching results.

2. 2. The system according to claim 1, wherein the analyzing means analyzes the job information using natural language processing and breaks it down into individual tasks.

3. 2. The system according to claim 1, wherein the matching means calculates a matching score based on the suitability of different tasks and conditions to generate a matching result.

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