System

Abstract

A system is provided.SOLUTION: A system comprising: means for a user to enter his or her resume; means for transmitting the resume to a server; means for the server to analyze the text of the resume; means for generating a revision suggestion based on the analysis; means for transmitting the revision suggestion to the user; and means for the user to revise the resume based on the revision suggestion.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] Job seekers often have difficulty determining whether their resumes are appropriate, and issues with proper formatting and grammar often prevent them from progressing smoothly through the hiring process. Resumes that are difficult to read are also difficult for recruiters to evaluate, potentially resulting in them overlooking suitable candidates. Furthermore, job seekers have difficulty obtaining feedback from recruiters, making it difficult for them to identify areas for improvement. To address these challenges, a method is needed that allows job seekers to efficiently improve their resumes. [Means for solving the problem]

[0005] The present invention provides a means for a user to input a resume and transmit the data to a server. The server includes means for analyzing the received resume text and generating revision suggestions based on the analysis results, allowing the user to improve their resume based on the revision suggestions. The server also includes means for analyzing the user's experience, skills, and desired job type and suggesting the most suitable job opportunities. The revision suggestions include suggesting new wording, correcting phrases, and restructuring sentences. This system allows job seekers to efficiently improve their resumes and smoothly progress through the hiring process.

[0006] "User" refers to an individual who enters a resume and uses the Application to improve it.

[0007] A "resume" is a document that lists information about a job seeker's career history, skills, work experience, etc.

[0008] "Server" refers to a computer system that receives user-submitted resumes, analyzes them, and generates suggested revisions.

[0009] "Means for inputting" refers to a method or device by which a user inputs a resume using a text editor or the like.

[0010] "Means for sending" refers to a communication function for sending resume data from the user's terminal to the server.

[0011] "Means for analyzing" refers to the technology that the server uses to analyze the text of the resume and extract problems with grammar and structure.

[0012] "Means for generating correction suggestions" refers to the function by which the server creates specific advice and suggestions for improving the resume based on the analysis results.

[0013] "Means for sending" refers to a communication function for sending the revision suggestions generated by the server to the user's terminal.

[0014] The "means for correcting" refers to a method or device for the user to correct and re-enter the resume based on suggestions from the server.

[0015] "Career" refers to information describing the job duties and career paths a user has had in the past.

[0016] "Skills" refers to information describing the skills and professional abilities that a user possesses.

[0017] "Desired occupation" refers to information indicating the occupation or job content desired by the user.

[0018] "Job Information" means detailed information about employment positions provided by companies or organizations. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0027] [First embodiment]

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

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

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

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

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

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

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

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

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

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

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

[0040] The present invention is a system that allows job seekers to input their resumes and improve them efficiently. This system involves sending the resumes entered by users to a server, which analyzes the contents and generates suggestions for revision. The user then revises the resume based on the suggestions, and the server then suggests the most suitable job information.

[0041] System Overview

[0042] Enter your resume

[0043] User:

[0044] A user enters their resume into a text editor in the application. For example, user A enters the following:

[0045] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[0046] Sending data

[0047] Device:

[0048] The resume data entered by the user is sent to the server using the HTTPS protocol to ensure a secure connection.

[0049] POST / api / submitResume HTTP / 1.1

[0050] Host: resume-advisor.example.com

[0051] Content-Type: application / json

[0052] {

[0053] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[0054] }

[0055] Data analysis

[0056] server:

[0057] The server analyzes the text of the received resume and utilizes the generative AI model GPT-3 (registered trademark) to evaluate grammar and structure.

[0058] For example, the following input is given to GPT-3 for analysis:

[0059] GPT-3: Rewrite the following resume section to be more professional and concise: I worked as a project manager for 5 years, listening to client requests, managing project progress and ensuring deadlines are met.

[0060] Generate correction suggestions

[0061] server:

[0062] The server generates revision suggestions for the user's resume based on the results of GPT-3 analysis. These revision suggestions include new wording suggestions, corrected phrases, and restructured sentences. For example, it generates the following revision suggestions:

[0063] Current position: Project Manager (5 years)

[0064] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0065] Submit and review your proposal

[0066] server:

[0067] The generated revision suggestions are sent to the user's terminal.

[0068] HTTP / 1.1 200 OK

[0069] Content-Type: application / json

[0070] {

[0071] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[0072] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[0073] }

[0074] User:

[0075] The user checks the suggestions from the server and corrects his / her resume. For example, he / she makes the following corrections according to the suggestions.

[0076] Current position: Project Manager (5 years)

[0077] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0078] Submit new data and reassess

[0079] Device:

[0080] The corrected resume data is sent to the server again.

[0081] POST / api / submitResume HTTP / 1.1

[0082] Host: resume-advisor.example.com

[0083] Content-Type: application / json

[0084] {

[0085] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[0086] }

[0087] server:

[0088] Re-analyze the received revised resume and evaluate whether there are any further improvements. If necessary, generate and send another revision proposal.

[0089] Providing job information

[0090] server:

[0091] The system analyzes the data registered by users about their career history, skills, and desired job type, and suggests the most suitable job information. For example, it generates the following job information:

[0092] json

[0093] {

[0094] "jobSuggestions": [

[0095] {

[0096] "company": "IT company B",

[0097] "position": "Project Manager",

[0098] "location": "Tokyo",

[0099] "description": "Responsible for managing large projects and customer relations."

[0100] }

[0101] ]

[0102] }

[0103] Device:

[0104] The proposed job listings are displayed to the user, who can then select the job that interests them and proceed with the application process.

[0105] The processing flow will be explained below.

[0106] Step 1:

[0107] A user enters a resume into a text editor within the application. For example, the user enters the following text:

[0108] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[0109] Step 2:

[0110] The terminal sends the resume data entered by the user to the server. The HTTPS protocol is used to ensure a secure connection. For example, the following JSON data is sent:

[0111] POST / api / submitResume HTTP / 1.1

[0112] Host: resume-advisor.example.com

[0113] Content-Type: application / json

[0114] {

[0115] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[0116] }

[0117] Step 3:

[0118] The server analyzes the text data of the resume it receives. First, the server converts the received data from JSON format to text data for analysis.

[0119] Step 4:

[0120] The server uses the generative AI model GPT-3 to evaluate the grammar and structure of the resume, providing prompts like the following to GPT-3:

[0121] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[0122] Step 5:

[0123] The server then uses the GPT-3 results to generate suggested revisions to the user's resume, including new wording suggestions, corrected phrases, and restructured sentences.

[0124] Current position: Project Manager (5 years)

[0125] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0126] Step 6:

[0127] The server generates correction suggestions and sends them to the user's device in JSON format.

[0128] HTTP / 1.1 200 OK

[0129] Content-Type: application / json

[0130] {

[0131] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[0132] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[0133] }

[0134] Step 7:

[0135] The user checks the suggestions from the server and corrects his / her resume. The user makes the following corrections according to the suggestions.

[0136] Current position: Project Manager (5 years)

[0137] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0138] Step 8:

[0139] The terminal transmits the corrected resume data to the server again.

[0140] POST / api / submitResume HTTP / 1.1

[0141] Host: resume-advisor.example.com

[0142] Content-Type: application / json

[0143] {

[0144] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[0145] }

[0146] Step 9:

[0147] The server re-analyzes the received revised resume and evaluates whether there are any further improvements, and if necessary, generates and sends another revision proposal.

[0148] Step 10:

[0149] The user enters data to register their career history, skills, and desired job type. For example, User A registers the following data.

[0150] {

[0151] "career": "5 years of experience as a project manager",

[0152] "skills": "Project management, customer relations, delivery management",

[0153] "desiredPosition": "Project Manager"

[0154] }

[0155] Step 11:

[0156] The server analyzes the user's career history, skills, and desired job type, and proposes the most suitable job information. For example, it generates the following job information:

[0157] {

[0158] "jobSuggestions": [

[0159] {

[0160] "company": "IT company B",

[0161] "position": "Project Manager",

[0162] "location": "Tokyo",

[0163] "description": "Responsible for managing large projects and customer relations."

[0164] }

[0165] ]

[0166] }

[0167] Step 12:

[0168] The device displays the suggested job listings to the user, who can then select the job that interests them and proceed with the application process.

[0169] Example 1

[0170] 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."

[0171] Conventional resume creation systems require users to manually edit resumes, which is time-consuming and labor-intensive. Finding appropriate job postings also requires users' own efforts. Furthermore, applying for a job without reviewing grammar and structure can reduce the effectiveness of job searches. Therefore, there is a need for a system that can efficiently improve resumes and provide optimal job postings.

[0172] 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.

[0173] In this invention, the server includes a means for a user to input their own resume, a means for transmitting the resume to the server using a data transmission device, a means for the server to analyze the resume text using a generative AI model, a means for generating revision suggestions based on the analysis results, a means for transmitting the revision suggestions to the user's terminal, and a means for the user to revise their resume based on the revision suggestions. This allows the user to quickly and efficiently improve their resume and receive optimal job information.

[0174] "User" refers to the individual or entity that creates, inputs, or modifies a resume.

[0175] "Resume" refers to a document that lists a user's work history, skills, achievements, qualifications, etc.

[0176] The "data transmission device" refers to hardware or software for transmitting the resume entered by the user to the server.

[0177] "Server" refers to a central processing unit that receives user-submitted resumes, analyzes them, and generates revision suggestions.

[0178] "Generative AI model" refers to an artificial intelligence platform that uses natural language processing technology to analyze resume text and generate revision suggestions.

[0179] "Analysis" refers to the process of using a generative AI model to evaluate the grammar, structure, and content of a resume to identify areas for improvement.

[0180] "Suggested revisions" refers to the resume improvement suggestions provided by the generative AI model based on the analysis results.

[0181] "Device" refers to the device (e.g., computer, tablet, smartphone, etc.) through which a user enters their resume and receives suggested revisions.

[0182] "Best-fit job information" refers to information about job opportunities selected based on the user's resume and registration information.

[0183] MODE FOR CARRYING OUT THE INVENTION

[0184] The present invention is a system for enabling job seekers to efficiently improve their resumes, which involves a series of processes in which a user inputs their resume, sends the data to a server, and the server analyzes it, generates suggestions for revision, and provides feedback to the user.

[0185] Hardware and software used

[0186] Hardware:

[0187] Devices: Computers, tablets, smartphones, etc.

[0188] Server: A central processing unit that performs high-performance data processing.

[0189] software:

[0190] Program: A custom application for sending, receiving, parsing resume data, and generating revision suggestions.

[0191] Generative AI model: An artificial intelligence platform that uses natural language processing technology, such as OpenAI's (registered trademark) GPT-3.

[0192] Specific operation of the system

[0193] User:

[0194] The user enters their resume into a text editor within the application, for example by entering the following:

[0195] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[0196] Device:

[0197] The terminal sends the entered resume to the server using the HTTPS protocol, with end-to-end encryption used during the transmission process to ensure data security.

[0198] server:

[0199] The server analyzes the text of the received resume. For this analysis, it uses the generative AI model GPT-3. The server starts the analysis by sending the following prompt to GPT-3:

[0200] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[0201] server:

[0202] Based on the analysis results of GPT-3, correction suggestions are generated. These correction suggestions include new wording suggestions, phrase corrections, and sentence restructuring. An example of a generated correction suggestion is as follows:

[0203] Current position: Project Manager (5 years)

[0204] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0205] server:

[0206] The generated revision suggestions are sent to the user's terminal, and feedback is provided for the user to re-revise their resume. The revised resume data is sent back to the server for re-evaluation.

[0207] server:

[0208] Finally, the app will suggest suitable job listings based on the user's resume and registered information, including details such as company name, position, location, and job description.

[0209] Specific examples

[0210] For example, if User A enters his / her resume and sends it with the following message, "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met," the server will analyze it using GPT-3, a generative AI model, and return the following suggested revisions to User A:

[0211] Current position: Project Manager (5 years)

[0212] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0213] User A then follows the suggestions to revise their resume and undergo further reevaluation to refine it to the best possible form. Ultimately, User A is presented with job information that best suits their background and skills, enabling them to efficiently search for a job.

[0214] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0215] Step 1: User enters resume

[0216] Input: User's resume text

[0217] Output: Input resume data

[0218] Specific behavior: A user enters their resume into a text editor in the application. For example, the user enters the following text:

[0219] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[0220] Step 2: Submit your resume

[0221] Input: User-entered resume data

[0222] Output: Resume data sent to the server

[0223] Specific operation: The terminal sends the resume data entered by the user to the server using the HTTPS protocol. The JSON format for sending is as follows:

[0224] POST / api / submitResume HTTP / 1.1

[0225] Host: resume-advisor.example.com

[0226] Content-Type: application / json

[0227] {

[0228] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[0229] }

[0230] Step 3: Analyze resume data

[0231] Input: Resume data sent to the server

[0232] Output: Generates analysis results AI model input data

[0233] Specific operation: The server analyzes the text of the received resume. This analysis is performed using OpenAI's generative AI model, GPT-3. The server sends the following prompt to GPT-3:

[0234] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[0235] Step 4: Generate correction suggestions

[0236] Input: Analysis results from a generative AI model

[0237] Output: Proposed correction data

[0238] Specific operation: The server generates correction suggestions based on the analysis results of GPT-3. These correction suggestions include new wording suggestions, phrase corrections, and sentence restructuring. For example, the following correction suggestions are generated:

[0239] Current position: Project Manager (5 years)

[0240] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0241] Step 5: Submit your proposed revision

[0242] Input: Proposed correction data

[0243] Output: Suggested correction data sent to the user's device

[0244] Specific operation: The server sends the generated revision suggestions to the user's device, after which the user can revise their resume based on the suggestions.

[0245] Step 6: User revises resume

[0246] Input: Suggested correction data sent to the user's device

[0247] Output: Corrected resume data

[0248] Specific operation: The user checks the suggestions from the server and modifies his / her resume. For example, he / she modifies his / her resume based on the suggestions as follows:

[0249] Current position: Project Manager (5 years)

[0250] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0251] Step 7: Resubmit your revised resume

[0252] Input: Revised resume data

[0253] Output: Resent resume data

[0254] Specific operation: The device sends the corrected resume data to the server again, again using the HTTPS protocol.

[0255] Step 8: Reassess your resume

[0256] Input: Resent resume data

[0257] Output: Secondary correction suggestions or evaluation data showing that no improvement is necessary

[0258] Specific behavior: The server re-analyzes the revised resume and either generates revision suggestions again or evaluates it as not requiring revision.

[0259] Step 9: Provide the best job offers

[0260] Input: Revised resume data and user registration information

[0261] Output: Optimal job posting data

[0262] Specific operation: The server will suggest the most suitable job information based on the user's revised resume and registered information. For example, the following job information will be generated.

[0263] Company Name: Technology Company

[0264] Job title: Project Manager

[0265] Location: Tokyo

[0266] Description: Responsible for managing large scale projects and customer relations.

[0267] This allows users to efficiently improve their resumes and find the best job opportunities.

[0268] (Application example 1)

[0269] 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."

[0270] In recent years, job seekers have been required to accurately and effectively describe their career history, but there is a lack of easy ways to do so. In particular, there is a need for a method that allows busy users, especially those in the midst of a job search, to create high-quality resumes without spending a lot of time. Furthermore, in order to quickly obtain appropriate job information, an advanced system that can perform detailed analysis of the user's career history and preferences is required. A new system that can solve these issues and improve user convenience is needed.

[0271] 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.

[0272] In this invention, the server includes means for a user to input their own resume, means for transmitting the resume to the server, means for the server to analyze the text of the resume, means for generating revision suggestions based on the analysis results, means for transmitting the revision suggestions to the user, means for the user to revise their resume based on the revision suggestions, means for converting voice input into text, and means for displaying the analysis results on the smart glasses. This allows the user to create a resume by voice input and further revise it while receiving feedback through the smart glasses, allowing them to easily and quickly obtain optimal job information.

[0273] "User" refers to an individual who uses the system to input or modify their resume.

[0274] A "resume" is a document that lists a user's work history, skills, career history, etc.

[0275] "Server" refers to a computer system that receives and analyzes data sent by users, and generates and returns suggested modifications.

[0276] "Voice input" is a method in which a user inputs information using voice.

[0277] "Text conversion" is the process of converting voice-input data into text form.

[0278] "Analysis means" refers to the function by which the server analyzes the resume, evaluates its contents, and identifies areas for improvement.

[0279] "Suggested revisions" refers to suggestions for improvements to the resume or new wording that the server provides to the user based on the analysis results.

[0280] "Smart glasses" are wearable devices that can visually display revision suggestions and other information to the user.

[0281] The present invention provides a system for users to efficiently improve their resumes. This system includes a series of processes, including voice input, text conversion, analysis, suggested revisions, feedback using smart glasses, and suggestion of optimal job information. An embodiment of this system will be described in detail below.

[0282] Voice to text conversion

[0283] The user uses the smart glasses to input voice data. For example, the user might say, "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met." This voice data is converted into text using the Google® Speech-to-Text API.

[0284] Submit your resume

[0285] The device then uses the HTTPS protocol to transmit the converted text data to a server that uses the SSL / TLS protocol to ensure a secure connection.

[0286] Data analysis

[0287] The server analyzes the received resume text data using a generative AI model (GPT-3). The following prompt sentence is used for the analysis:

[0288] "Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years. I listened to client requests, managed project progress, and ensured deadlines were met."

[0289] Generation of correction suggestions and feedback

[0290] The server generates correction suggestions based on the results of GPT-3 analysis. For example, these correction suggestions may look like this:

[0291] Current position: Project Manager (5 years) Responsibilities: Understand customer requirements, manage project progress and ensure delivery deadlines.

[0292] The generated revision suggestions are visually fed back to the user through the smart glasses, allowing the user to review them and revise their resume.

[0293] Providing job information

[0294] The server generates optimal job information based on the user's revised resume and registered data (career history, skills, desired job type). For example, it provides the following job information:

[0295] "Company: IT Company B Position: Project Manager Location: Tokyo Description: Responsible for managing large-scale projects and dealing with customers."

[0296] This job information is visually displayed to the user using the smart glasses, allowing the user to select jobs that interest them and proceed with the application process.

[0297] In this way, the present invention allows users to effortlessly improve their resumes and quickly obtain the most suitable job information.

[0298] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0299] Step 1:

[0300] The user inputs voice data through the smart glasses. For example, the user might say, "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured delivery deadlines were met." This input voice data is captured by a microphone built into the smart glasses.

[0301] Step 2:

[0302] The device (smart glasses) converts the input voice data into text. To do this, the device calls the Google Speech-to-Text API to convert the voice data into text format. The input is the captured voice data, and the output is the text data corresponding to the voice content.

[0303] Step 3:

[0304] The terminal sends text data to the server using the HTTPS protocol to ensure confidentiality and integrity of the data. The input is the text data converted from the voice, and the output is a response confirming the data sent to the server.

[0305] Step 4:

[0306] The server analyzes the received text data. A generative AI model (GPT-3) is used for this analysis. Specifically, the server provides the text data to GPT-3 using the following prompt: "Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met." The input is the received text data, and the output is the correction suggestions generated by the analysis.

[0307] Step 5:

[0308] The server sends the generated correction suggestions back to the device. This transmission is also done using the HTTPS protocol. The input is the analysis result by GPT-3, i.e., the correction suggestions, and the output is the correction suggestions data sent to the device.

[0309] Step 6:

[0310] The terminal displays the suggested revisions on the display of the smart glasses. The user checks this visual feedback and revises the resume content as necessary. The input is the suggested revision data received from the server, and the output is the suggested revisions displayed on the display of the smart glasses.

[0311] Step 7:

[0312] The user corrects the resume based on the suggested corrections and sends it back to the server. The input is the resume text corrected by the user, and the output is the corrected data sent to the server.

[0313] Step 8:

[0314] The server generates optimal job listings based on the user's revised resume and registered data (career history, skills, desired job type). This is done using GPT-3 again. The input is the user's revised resume and registered information, and the output is the generated job listing.

[0315] Step 9:

[0316] The server sends the generated job information to the terminal, and the terminal displays the job information on the display of the smart glasses. The input is the generated job information, and the output is the job information visually displayed on the display of the smart glasses.

[0317] In this way, the present invention allows users to effortlessly improve their resumes and quickly obtain the most suitable job information.

[0318] 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.

[0319] The present invention provides a system that allows job seekers to input their resumes and efficiently improve them, and further combines it with an emotion engine that recognizes the user's emotions. This system transmits the resume entered by the user to a server, which analyzes its contents and generates revision suggestions. The system includes a process in which the user revises the resume based on the suggestions, and the server then suggests optimal job information. Furthermore, the emotion engine recognizes the user's emotions and reflects them in the revision suggestions, providing more appropriate support.

[0320] System Overview

[0321] Enter your resume

[0322] User:

[0323] A user enters their resume into a text editor in the application. For example, user A enters the following:

[0324] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[0325] Sending data

[0326] Device:

[0327] The resume data entered by the user is sent to the server. The HTTPS protocol is used to ensure a secure connection. For example, the following JSON data is sent:

[0328] POST / api / submitResume HTTP / 1.1

[0329] Host: resume-advisor.example.com

[0330] Content-Type: application / json

[0331] {

[0332] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[0333] }

[0334] Data analysis

[0335] server:

[0336] The server analyzes the received resume text data. First, the server converts the received data from JSON format to text data for analysis.

[0337] Next, we use GPT-3, a generative AI model, to evaluate the grammar and structure of the resume. For example, we give GPT-3 the following input to analyze it:

[0338] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[0339] Generate correction suggestions

[0340] server:

[0341] The server generates revision suggestions for the user's resume based on the results of GPT-3 analysis. These revision suggestions include new wording suggestions, corrected phrases, and restructured sentences. For example, it generates the following revision suggestions:

[0342] Current position: Project Manager (5 years)

[0343] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0344] Emotion recognition by emotion engine

[0345] Emotion Engine:

[0346] The emotion engine analyzes emotions based on user input and operational context, for example, analyzing how users react to suggested edits (e.g., frustration, joy, confusion) in real time.

[0347] Adjusting proposed changes

[0348] server:

[0349] The server adjusts the tone and content of the correction suggestions based on the output of the emotion engine. For example, if the user is feeling stressed, it will take a softer approach to the suggestions.

[0350] Below is an example of an adjustment suggested by the emotion engine.

[0351] Current position: Project Manager (5 years)

[0352] Responsibilities: I was responsible for properly understanding the client's requirements, managing the project progress smoothly, and ensuring delivery deadlines were met.

[0353] Submit and review your proposal

[0354] server:

[0355] The generated correction suggestions are sent to the user's device in JSON format.

[0356] HTTP / 1.1 200 OK

[0357] Content-Type: application / json

[0358] {

[0359] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[0360] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[0361] }

[0362] User:

[0363] The user checks the suggestions from the server and corrects his / her resume. For example, he / she makes the following corrections according to the suggestions.

[0364] Current position: Project Manager (5 years)

[0365] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0366] Submit new data and reassess

[0367] Device:

[0368] The corrected resume data is sent to the server again.

[0369] POST / api / submitResume HTTP / 1.1

[0370] Host: resume-advisor.example.com

[0371] Content-Type: application / json

[0372] {

[0373] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[0374] }

[0375] server:

[0376] Re-analyze the received revised resume and evaluate whether there are any further improvements. If necessary, generate and send another revision proposal.

[0377] Providing job information

[0378] server:

[0379] The user enters data to register their career history, skills, and desired job type. For example, User A registers the following data.

[0380] {

[0381] "career": "5 years of experience as a project manager",

[0382] "skills": "Project management, customer relations, delivery management",

[0383] "desiredPosition": "Project Manager"

[0384] }

[0385] server:

[0386] The server analyzes the user's career history, skills, and desired job type, and proposes the most suitable job information. For example, it generates the following job information:

[0387] {

[0388] "jobSuggestions": [

[0389] {

[0390] "company": "IT company B",

[0391] "position": "Project Manager",

[0392] "location": "Tokyo",

[0393] "description": "Responsible for managing large projects and customer relations."

[0394] }

[0395] ]

[0396] }

[0397] Device:

[0398] The proposed job listings are displayed to the user, who can then select the job that interests them and proceed with the application process.

[0399] The processing flow will be explained below.

[0400] Step 1:

[0401] A user enters a resume into a text editor within the application. For example, the user enters the following text:

[0402] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[0403] Step 2:

[0404] The terminal sends the resume data entered by the user to the server. The HTTPS protocol is used to ensure a secure connection. For example, the following JSON data is sent:

[0405] POST / api / submitResume HTTP / 1.1

[0406] Host: resume-advisor.example.com

[0407] Content-Type: application / json

[0408] {

[0409] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[0410] }

[0411] Step 3:

[0412] The server analyzes the text data of the resume it receives. First, the server converts the received data from JSON format to text data for analysis.

[0413] Step 4:

[0414] The server uses the generative AI model GPT-3 to evaluate the grammar and structure of the resume. For example, it gives prompts like the following to GPT-3:

[0415] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[0416] Step 5:

[0417] The server generates revision suggestions for the user's resume based on the GPT-3 response. These revision suggestions include new wording suggestions, phrase corrections, and sentence restructuring. For example, the following revision suggestions are generated:

[0418] Current position: Project Manager (5 years)

[0419] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0420] Step 6:

[0421] The emotion engine analyzes emotions based on the user's input and operational status. For example, it analyzes in real time whether the user is feeling stressed about the suggested corrections.

[0422] Step 7:

[0423] The server adjusts the tone and content of the correction suggestions based on the output of the emotion engine. For example, if the user is feeling stressed, it will adopt a softer tone approach. Below is an example of an adjusted correction suggestion.

[0424] Current position: Project Manager (5 years)

[0425] Responsibilities: I was responsible for properly understanding the client's requirements, managing the project progress smoothly, and ensuring delivery deadlines were met.

[0426] Step 8:

[0427] The server generates correction suggestions and sends them to the user's device in JSON format.

[0428] HTTP / 1.1 200 OK

[0429] Content-Type: application / json

[0430] {

[0431] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[0432] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[0433] }

[0434] Step 9:

[0435] The user checks the suggestions from the server and corrects the resume. For example, the user corrects the resume as follows according to the suggestions.

[0436] Current position: Project Manager (5 years)

[0437] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0438] Step 10:

[0439] The terminal transmits the corrected resume data to the server again.

[0440] POST / api / submitResume HTTP / 1.1

[0441] Host: resume-advisor.example.com

[0442] Content-Type: application / json

[0443] {

[0444] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[0445] }

[0446] Step 11:

[0447] The server re-analyzes the received revised resume and evaluates whether there are any further improvements, and if necessary, generates and sends another revision proposal.

[0448] Step 12:

[0449] The user enters data to register their career history, skills, and desired job type. For example, User A registers the following data.

[0450] {

[0451] "career": "5 years of experience as a project manager",

[0452] "skills": "Project management, customer relations, delivery management",

[0453] "desiredPosition": "Project Manager"

[0454] }

[0455] Step 13:

[0456] The server analyzes the user's career history, skills, and desired job type, and proposes the most suitable job information. For example, it generates the following job information:

[0457] {

[0458] "jobSuggestions": [

[0459] {

[0460] "company": "IT company",

[0461] "position": "Project Manager",

[0462] "location": "Tokyo",

[0463] "description": "Responsible for managing large projects and customer relations."

[0464] }

[0465] ]

[0466] }

[0467] Step 14:

[0468] The device displays the suggested job listings to the user, who can then select the job that interests them and proceed with the application process.

[0469] Example 2

[0470] 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."

[0471] Conventional resume creation support systems lack the functionality to automatically correct and optimize the content entered by the user, and do not provide support that takes the user's emotions into consideration. This can cause users to feel stressed. Furthermore, the lack of a function to suggest optimal job opportunities poses a challenge, making job searches less efficient.

[0472] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0473] In this invention, the server includes: means for a user to input their resume; means for transmitting the resume to the server; means for the server to analyze the text of the resume; means for generating revision suggestions based on the analysis results using a generative AI model; means including an emotion recognition engine that recognizes the user's emotions; means for adjusting the revision suggestions based on the output of the emotion recognition engine; means for transmitting the revision suggestions to the user; and means for the user to revise their resume based on the revision suggestions. This makes it possible to efficiently revise and optimize the user's resume, provide support that takes the user's emotions into consideration, and further, by suggesting optimal employment opportunities, enable efficient job hunting.

[0474] "User" refers to an individual who enters a resume and receives suggested revisions.

[0475] "Terminal" refers to an electronic device that allows a user to input a resume and transmit and receive data to and from a server.

[0476] "Server" refers to the computer system that analyzes resumes, generates revision suggestions, recognizes emotions, and makes job suggestions.

[0477] A "resume" refers to a document that lists a user's work history, skills, responsibilities, etc.

[0478] "Generative AI model" refers to the artificial intelligence algorithm used to analyze the content of a resume and generate suggested revisions.

[0479] An "emotion recognition engine" refers to a system that analyzes a user's emotions in real time and uses them to adjust suggested corrections.

[0480] "Suggested revisions" refers to the revisions the generative AI model suggests for improvement after evaluating the grammar and structure of the resume.

[0481] "Job information" refers to information about job opportunities suggested based on the user's career history, skills, and desired job type.

[0482] "Analysis" refers to the process of breaking down the content of a resume and evaluating its grammar and structure.

[0483] "Secure Connection" means an encrypted network connection for secure data communication.

[0484] The present invention relates to a system for efficiently improving a resume and providing support that takes into account the user's feelings. Specifically, the system involves a series of processes: inputting a user's resume, analyzing it, generating revision suggestions, and suggesting optimal job information.

[0485] To implement this system, the following hardware and software are used.

[0486] Hardware and software used

[0487] 1. Terminal: An electronic device on which a user inputs their resume and sends and receives data to and from the server. Examples include a PC or smartphone.

[0488] 2. Server: A computer system that analyzes resumes, generates revision suggestions, recognizes emotions, and proposes job information. The server is equipped with a high-performance CPU and large-capacity memory, and is installed with a database management system and an AI model operation environment.

[0489] 3. Generative AI model: An artificial intelligence algorithm used to analyze resume content and generate revision suggestions. A specific example is GPT-3 (Generative Pre-trained Transformer 3).

[0490] 4. Emotion Recognition Engine: A system that analyzes user emotions in real time and uses them to adjust revision suggestions. Software that implements specific emotion recognition algorithms is required.

[0491] Example of a system

[0492] Enter your resume

[0493] User: Enter their resume details into the text editor within the application. For example, enter the following:

[0494] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[0495] Sending data

[0496] Terminal: The resume data entered by the user is sent to the server, using the HTTPS protocol to ensure a secure connection.

[0497] Data analysis

[0498] Server: To analyze the received resume text data, the server converts the received data from JSON format to text data for analysis. Next, it uses the generative AI model GPT-3 to evaluate the grammar and structure. For example, it provides the following prompt sentence to GPT-3:

[0499] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[0500] Generate correction suggestions

[0501] Server: Based on the results of GPT-3 analysis, the server generates suggested revisions to the resume. For example, this includes suggesting new wording, correcting phrases, and restructuring sentences. Specific examples of suggested revisions include:

[0502] Current position: Project Manager (5 years)

[0503] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0504] Emotion recognition using an emotion recognition engine

[0505] Emotion Recognition Engine: Analyzes the user's reactions to suggested revisions. The emotion recognition engine recognizes the user's emotions, such as frustration, joy, and confusion, in real time.

[0506] Adjusting proposed changes

[0507] Server: Based on the output of the emotion recognition engine, the tone and content of the correction suggestions are adjusted. For example, if the user is feeling stressed, the suggestion is softened by the following:

[0508] Current position: Project Manager (5 years)

[0509] Responsibilities: I was responsible for properly understanding the client's requirements, managing the project progress smoothly, and ensuring delivery deadlines were met.

[0510] Submit and review your proposal

[0511] Server: The generated revision suggestions are sent in JSON format to the user's device. The user checks the revision suggestions from the server and revise their resume based on them.

[0512] In this way, the system of the present invention allows users to efficiently improve their resumes and obtain optimal job information while receiving appropriate support using emotion recognition.

[0513] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0514] Step 1: Enter your resume

[0515] User: Enter your resume into the text editor within the application. For example, enter the following:

[0516] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[0517] Input: The action of a user typing their resume into a text editor.

[0518] Output: The resume text saved in a text editor.

[0519] Step 2: Sending data

[0520] Terminal: The text data of the entered resume is sent to the server using the HTTPS protocol to ensure a secure connection.

[0521] json

[0522] POST / api / submitResume HTTP / 1.1

[0523] Host: resume-advisor.example.com

[0524] Content-Type: application / json

[0525] {

[0526] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[0527] }

[0528] Input: Resume data in a text editor.

[0529] Output: Text data of the submitted resume.

[0530] Step 3: Analyze the data

[0531] Server: Converts the received resume text data from JSON format to text data for analysis. Next, it uses the generative AI model GPT-3 to evaluate grammar and structure.

[0532] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[0533] Input: JSON data of the submitted resume.

[0534] Output: Analysis results by GPT-3.

[0535] Step 4: Generate correction suggestions

[0536] Server: Generates correction suggestions based on the results of GPT-3 analysis, such as proposing new wording or restructuring sentences.

[0537] Current position: Project Manager (5 years)

[0538] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0539] Input: Analysis results by GPT-3.

[0540] Output: Text data of suggested corrections.

[0541] Step 5: Emotion recognition by the emotion recognition engine

[0542] Emotion recognition engine: Analyzes emotions based on user input and operation status. For example, it analyzes how users react to suggested corrections (e.g., irritation, joy, confusion) in real time.

[0543] Input: User response data.

[0544] Output: User sentiment analysis results.

[0545] Step 6: Adjust the proposed changes

[0546] Server: Based on the output of the emotion recognition engine, the tone and content of the correction suggestions are adjusted. For example, if the user is feeling stressed, the tone of the suggestions is softened.

[0547] Current position: Project Manager (5 years)

[0548] Responsibilities: I was responsible for properly understanding the client's requirements, managing the project progress smoothly, and ensuring delivery deadlines were met.

[0549] Input: User sentiment analysis results, initial correction suggestions.

[0550] Output: Text data with sentiment-sensitive revision suggestions.

[0551] Step 7: Submit and review your proposal

[0552] Server: The generated correction suggestions are sent to the user's device in JSON format.

[0553] json

[0554] HTTP / 1.1 200 OK

[0555] Content-Type: application / json

[0556] {

[0557] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[0558] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[0559] }

[0560] User: Check the suggested revisions from the server and revise the resume based on them.

[0561] Current position: Project Manager (5 years)

[0562] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0563] Input: Emotion-sensitive revision suggestions.

[0564] Output: The corrected resume text data.

[0565] Step 8: Submit new data and reassess

[0566] Terminal: Send the corrected resume data to the server again.

[0567] json

[0568] POST / api / submitResume HTTP / 1.1

[0569] Host: resume-advisor.example.com

[0570] Content-Type: application / json

[0571] {

[0572] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[0573] }

[0574] Server: Re-analyzes the resubmitted revised resume and evaluates whether there are any further improvements needed. If necessary, generates revision suggestions again and sends them to the user.

[0575] Input: Text data of the revised resume.

[0576] Output: Text data of the final revision suggestions.

[0577] Step 9: Post a job offer

[0578] Server: Analyzes the data registered by users regarding their career history, skills, and desired job type, and proposes the most suitable job information. For example, it generates the following job information:

[0579] json

[0580] {

[0581] "jobSuggestions": [

[0582] {

[0583] "company": "IT company",

[0584] "position": "Project Manager",

[0585] "location": "Tokyo",

[0586] "description": "Responsible for managing large projects and customer relations."

[0587] }

[0588] ]

[0589] }

[0590] Input: User's background, skills, and desired job data.

[0591] Output: Data suggesting the best job listings.

[0592] Terminal: Displays suggested job information to the user, who can then select the job they are interested in and proceed with the application process.

[0593] (Application example 2)

[0594] 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."

[0595] In today's world, people are expected to be able to effectively express their thoughts and opinions and communicate better with others. However, opinions are often not conveyed properly due to individual expressiveness and emotional influences. In addition, when a user receives necessary suggestions or feedback, it is necessary to appropriately adjust the suggestions based on the detected user's emotions. Therefore, this invention aims to provide a system that supports more appropriate and effective communication by analyzing users' opinions and impressions in real time, improving the content, and utilizing an emotion engine to suggest modifications that match the user's emotions.

[0596] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to input their own information, means for transmitting the information to the server, means for the server to analyze the text of the information, means for generating a revision suggestion based on the analysis result, means for transmitting the revision suggestion to the user, means for the user to correct their information based on the revision suggestion, and means for recognizing the user's emotions using an emotion engine and adjusting the revision suggestion. This allows the user to effectively improve their own information while receiving suggestions that take their emotions into consideration, thereby improving the quality of self-expression and communication.

[0597] "User" refers to an individual who enters their information and uses the system.

[0598] "Information" refers to opinions, impressions, or other written content entered by the user.

[0599] A "server" is a computer system that receives and analyzes user-submitted information, and generates and transmits revision suggestions.

[0600] "Parsing" is the process of evaluating the grammar, structure, and content of user-entered information and generating appropriate correction suggestions.

[0601] "Suggested corrections" are suggestions for improving the information entered by the user, including new wording suggestions, corrected phrases, and restructured sentences.

[0602] An "emotion engine" is software or hardware that recognizes and analyzes a user's emotions.

[0603] "Adjusting" refers to appropriately changing the tone and content of the revision suggestion depending on the user's emotion as recognized by the emotion engine.

[0604] This invention is a system that allows users to input their own information (opinions, impressions, etc.) and efficiently improve it. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides more appropriate support.

[0605] System Overview

[0606] Enter and submit information

[0607] A user inputs their information into a text editor via a device such as a smartphone or smart glasses. For example, a user inputs their review of a movie as follows:

[0608] "This movie was moving, but I wish the climax had been a little more impressive."

[0609] The information entered by the user is sent to the server via a secure protocol (e.g., HTTPS).

[0610] Analysis of information

[0611] The server analyzes the received information. First, it converts the received data into text data, and then uses a generative AI model (e.g., GPT-3) to evaluate the grammar and structure of the information. For example, it analyzes the information by giving GPT-3 the following prompt sentence:

[0612] "Please make your comments more professional and concise: The film was moving, but I wish the climax was a little more impactful."

[0613] Generate correction suggestions

[0614] Based on the analysis results, the server will suggest how to correct the user's information. The suggested corrections include new wording, corrected phrases, and restructured sentences. For example, the server will generate the following correction suggestions:

[0615] "The film was very moving, but I thought there was room for an even stronger climax."

[0616] Emotion recognition and regulation with emotion engine

[0617] Emotion engines (e.g., EmoReact) analyze user emotions based on their input and operational context. For example, if a user is frustrated, the tone of the suggested corrections will be softened. Below is an example of an adjustment made by an emotion engine.

[0618] "The film was very moving, but I thought there was room for the climax to be even more impactful. I agree with you."

[0619] Submit and review your proposal

[0620] The server sends the generated revision suggestions to the user, who then confirms and corrects them.

[0621] Hardware and software used

[0622] Hardware: Smartphones, smart glasses, servers.

[0623] Software: GPT-3 (generative AI model), EmoReact (emotion engine), secure data transmission via HTTPS protocol.

[0624] A concrete example of a prompt from a generative AI model

[0625] 1. Prompts to improve your opinion:

[0626] "Please make your comments more professional and concise: The film was moving, but I wish the climax was a little more impactful."

[0627] 2. Emotion-awareness regulation reflection prompt:

[0628] "Please tone it down if the user is stressed: This movie was moving, but I wish the climax was a little more impactful. I agree with you."

[0629] In this way, users can effectively improve their information and receive appropriate emotional support.

[0630] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0631] Step 1:

[0632] A user inputs their information through a text editor on a smartphone or smart glasses. For example, a user may write their impression of a movie as, "This movie was moving, but I wish the climax had been more memorable."

[0633] input:

[0634] Text data of user opinions and impressions.

[0635] output:

[0636] The entered information is stored on the terminal and is ready to be sent to the next processing step.

[0637] Step 2:

[0638] The device securely transmits the entered information to the server using the HTTPS protocol, and the transmitted data is packaged in JSON format.

[0639] input:

[0640] Text data entered by the user.

[0641] output:

[0642] Text data sent to a server over a secure protocol.

[0643] Specific behavior:

[0644] The terminal converts the user's text data into JSON format and sends it to the server using the HTTPS protocol.

[0645] Step 3:

[0646] The server converts the received text data into text for analysis and feeds it to a generative AI model (e.g., GPT-3) to evaluate grammar and composition. For example, it uses a prompt sentence such as, "Please make the provided opinion more professional and concise: This movie was moving, but I think the climax could have been more impressive."

[0647] input:

[0648] Text data received in JSON format.

[0649] output:

[0650] Analysis results (correction suggestions) generated by the generative AI model.

[0651] Specific behavior:

[0652] The server extracts text from the JSON data and inputs it to GPT-3 along with a prompt sentence for analysis.

[0653] Step 4:

[0654] The server generates suggestions for correcting the user's information based on the analysis, including new wording, corrected phrases, and restructured sentences.

[0655] input:

[0656] Text data analyzed by a generative AI model.

[0657] output:

[0658] Text data of the proposed correction.

[0659] Specific behavior:

[0660] Based on the analysis results, the server generates text that suggests new phrases, corrections to phrases, and restructuring of sentences.

[0661] Step 5:

[0662] The server uses an emotion engine (e.g., EmoReact) to recognize the user's emotions in real time and adjust the tone and content of the correction suggestions accordingly, for example, to tone down the suggestion if the user is annoyed.

[0663] input:

[0664] Emotional data based on user input and operation status.

[0665] output:

[0666] Text data with sentiment-adjusted revision suggestions.

[0667] Specific behavior:

[0668] The server uses emotion recognition software to analyze the user's emotions and adjusts the tone and content of the revision suggestions based on the results.

[0669] Step 6:

[0670] The server then sends the generated correction suggestions to the user's device via a secure protocol, packaged in JSON format.

[0671] input:

[0672] Text data of the adjusted correction proposal.

[0673] output:

[0674] The suggested fixes sent to the user's device.

[0675] Specific behavior:

[0676] The server converts the proposed revisions into JSON format and sends them to the terminal using the HTTPS protocol.

[0677] Step 7:

[0678] The user checks the received correction suggestions and corrects his / her information. Based on the correction suggestions, the user updates the information.

[0679] input:

[0680] Text data of the suggested revision sent from the server.

[0681] output:

[0682] The text data of the corrected information.

[0683] Specific behavior:

[0684] The user reviews the received revision suggestions and updates the information by applying new wording, correcting phrases, and restructuring the sentence.

[0685] 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.

[0686] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0687] 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.

[0688] [Second embodiment]

[0689] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0690] 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.

[0691] 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).

[0692] 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.

[0693] 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.

[0694] 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).

[0695] 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.

[0696] 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.

[0697] 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.

[0698] 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.

[0699] 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.

[0700] 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."

[0701] The present invention is a system that allows job seekers to input their resumes and improve them efficiently. This system involves sending the resumes entered by users to a server, which analyzes the contents and generates suggestions for revision. The user then revises the resume based on the suggestions, and the server then suggests the most suitable job information.

[0702] System Overview

[0703] Enter your resume

[0704] User:

[0705] A user enters their resume into a text editor in the application. For example, user A enters the following:

[0706] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[0707] Sending data

[0708] Device:

[0709] The resume data entered by the user is sent to the server using the HTTPS protocol to ensure a secure connection.

[0710] POST / api / submitResume HTTP / 1.1

[0711] Host: resume-advisor.example.com

[0712] Content-Type: application / json

[0713] {

[0714] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[0715] }

[0716] Data analysis

[0717] server:

[0718] The server analyzes the text of the received resume and utilizes the generative AI model GPT-3 to evaluate grammar and structure.

[0719] For example, the following input is given to GPT-3 for analysis:

[0720] GPT-3: Rewrite the following resume section to be more professional and concise: I worked as a project manager for 5 years, listening to client requests, managing project progress and ensuring deadlines are met.

[0721] Generate correction suggestions

[0722] server:

[0723] The server generates revision suggestions for the user's resume based on the results of GPT-3 analysis. These revision suggestions include new wording suggestions, corrected phrases, and restructured sentences. For example, it generates the following revision suggestions:

[0724] Current position: Project Manager (5 years)

[0725] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0726] Submit and review your proposal

[0727] server:

[0728] The generated revision suggestions are sent to the user's terminal.

[0729] HTTP / 1.1 200 OK

[0730] Content-Type: application / json

[0731] {

[0732] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[0733] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[0734] }

[0735] User:

[0736] The user checks the suggestions from the server and corrects his / her resume. For example, he / she makes the following corrections according to the suggestions.

[0737] Current position: Project Manager (5 years)

[0738] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0739] Submit new data and reassess

[0740] Device:

[0741] The corrected resume data is sent to the server again.

[0742] POST / api / submitResume HTTP / 1.1

[0743] Host: resume-advisor.example.com

[0744] Content-Type: application / json

[0745] {

[0746] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[0747] }

[0748] server:

[0749] Re-analyze the received revised resume and evaluate whether there are any further improvements. If necessary, generate and send another revision proposal.

[0750] Providing job information

[0751] server:

[0752] The system analyzes the data registered by users about their career history, skills, and desired job type, and suggests the most suitable job information. For example, it generates the following job information:

[0753] json

[0754] {

[0755] "jobSuggestions": [

[0756] {

[0757] "company": "IT company B",

[0758] "position": "Project Manager",

[0759] "location": "Tokyo",

[0760] "description": "Responsible for managing large projects and customer relations."

[0761] }

[0762] ]

[0763] }

[0764] Device:

[0765] The proposed job listings are displayed to the user, who can then select the job that interests them and proceed with the application process.

[0766] The processing flow will be explained below.

[0767] Step 1:

[0768] A user enters a resume into a text editor within the application. For example, the user enters the following text:

[0769] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[0770] Step 2:

[0771] The terminal sends the resume data entered by the user to the server. The HTTPS protocol is used to ensure a secure connection. For example, the following JSON data is sent:

[0772] POST / api / submitResume HTTP / 1.1

[0773] Host: resume-advisor.example.com

[0774] Content-Type: application / json

[0775] {

[0776] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[0777] }

[0778] Step 3:

[0779] The server analyzes the text data of the resume it receives. First, the server converts the received data from JSON format to text data for analysis.

[0780] Step 4:

[0781] The server uses the generative AI model GPT-3 to evaluate the grammar and structure of the resume, providing prompts like the following to GPT-3:

[0782] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[0783] Step 5:

[0784] The server then uses the GPT-3 results to generate suggested revisions to the user's resume, including new wording suggestions, corrected phrases, and restructured sentences.

[0785] Current position: Project Manager (5 years)

[0786] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0787] Step 6:

[0788] The server generates correction suggestions and sends them to the user's device in JSON format.

[0789] HTTP / 1.1 200 OK

[0790] Content-Type: application / json

[0791] {

[0792] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[0793] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[0794] }

[0795] Step 7:

[0796] The user checks the suggestions from the server and corrects his / her resume. The user makes the following corrections according to the suggestions.

[0797] Current position: Project Manager (5 years)

[0798] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0799] Step 8:

[0800] The terminal transmits the corrected resume data to the server again.

[0801] POST / api / submitResume HTTP / 1.1

[0802] Host: resume-advisor.example.com

[0803] Content-Type: application / json

[0804] {

[0805] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[0806] }

[0807] Step 9:

[0808] The server re-analyzes the received revised resume and evaluates whether there are any further improvements, and if necessary, generates and sends another revision proposal.

[0809] Step 10:

[0810] The user enters data to register their career history, skills, and desired job type. For example, User A registers the following data.

[0811] {

[0812] "career": "5 years of experience as a project manager",

[0813] "skills": "Project management, customer relations, delivery management",

[0814] "desiredPosition": "Project Manager"

[0815] }

[0816] Step 11:

[0817] The server analyzes the user's career history, skills, and desired job type, and proposes the most suitable job information. For example, it generates the following job information:

[0818] {

[0819] "jobSuggestions": [

[0820] {

[0821] "company": "IT company B",

[0822] "position": "Project Manager",

[0823] "location": "Tokyo",

[0824] "description": "Responsible for managing large projects and customer relations."

[0825] }

[0826] ]

[0827] }

[0828] Step 12:

[0829] The device displays the suggested job listings to the user, who can then select the job that interests them and proceed with the application process.

[0830] Example 1

[0831] 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."

[0832] Conventional resume creation systems require users to manually edit resumes, which is time-consuming and labor-intensive. Finding appropriate job postings also requires users' own efforts. Furthermore, applying for a job without reviewing grammar and structure can reduce the effectiveness of job searches. Therefore, there is a need for a system that can efficiently improve resumes and provide optimal job postings.

[0833] 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.

[0834] In this invention, the server includes a means for a user to input their own resume, a means for transmitting the resume to the server using a data transmission device, a means for the server to analyze the resume text using a generative AI model, a means for generating revision suggestions based on the analysis results, a means for transmitting the revision suggestions to the user's terminal, and a means for the user to revise their resume based on the revision suggestions. This allows the user to quickly and efficiently improve their resume and receive optimal job information.

[0835] "User" refers to the individual or entity that creates, inputs, or modifies a resume.

[0836] "Resume" refers to a document that lists a user's work history, skills, achievements, qualifications, etc.

[0837] The "data transmission device" refers to hardware or software for transmitting the resume entered by the user to the server.

[0838] "Server" refers to a central processing unit that receives user-submitted resumes, analyzes them, and generates revision suggestions.

[0839] "Generative AI model" refers to an artificial intelligence platform that uses natural language processing technology to analyze resume text and generate revision suggestions.

[0840] "Analysis" refers to the process of using a generative AI model to evaluate the grammar, structure, and content of a resume to identify areas for improvement.

[0841] "Suggested revisions" refers to the resume improvement suggestions provided by the generative AI model based on the analysis results.

[0842] "Device" refers to the device (e.g., computer, tablet, smartphone, etc.) through which a user enters their resume and receives suggested revisions.

[0843] "Best-fit job information" refers to information about job opportunities selected based on the user's resume and registration information.

[0844] MODE FOR CARRYING OUT THE INVENTION

[0845] The present invention is a system for enabling job seekers to efficiently improve their resumes, which involves a series of processes in which a user inputs their resume, sends the data to a server, and the server analyzes it, generates suggestions for revision, and provides feedback to the user.

[0846] Hardware and software used

[0847] Hardware:

[0848] Devices: Computers, tablets, smartphones, etc.

[0849] Server: A central processing unit that performs high-performance data processing.

[0850] software:

[0851] Program: A custom application for sending, receiving, parsing resume data, and generating revision suggestions.

[0852] Generative AI model: An artificial intelligence platform that uses natural language processing techniques such as OpenAI's GPT-3.

[0853] Specific operation of the system

[0854] User:

[0855] The user enters their resume into a text editor within the application, for example by entering the following:

[0856] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[0857] Device:

[0858] The terminal sends the entered resume to the server using the HTTPS protocol, with end-to-end encryption used during the transmission process to ensure data security.

[0859] server:

[0860] The server analyzes the text of the received resume. For this analysis, it uses the generative AI model GPT-3. The server starts the analysis by sending the following prompt to GPT-3:

[0861] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[0862] server:

[0863] Based on the analysis results of GPT-3, correction suggestions are generated. These correction suggestions include new wording suggestions, phrase corrections, and sentence restructuring. An example of a generated correction suggestion is as follows:

[0864] Current position: Project Manager (5 years)

[0865] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0866] server:

[0867] The generated revision suggestions are sent to the user's terminal, and feedback is provided for the user to re-revise their resume. The revised resume data is sent back to the server for re-evaluation.

[0868] server:

[0869] Finally, the app will suggest suitable job listings based on the user's resume and registered information, including details such as company name, position, location, and job description.

[0870] Specific examples

[0871] For example, if User A enters his / her resume and sends it with the following message, "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met," the server will analyze it using GPT-3, a generative AI model, and return the following suggested revisions to User A:

[0872] Current position: Project Manager (5 years)

[0873] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0874] User A then follows the suggestions to revise their resume and undergo further reevaluation to refine it to the best possible form. Ultimately, User A is presented with job information that best suits their background and skills, enabling them to efficiently search for a job.

[0875] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0876] Step 1: User enters resume

[0877] Input: User's resume text

[0878] Output: Input resume data

[0879] Specific behavior: A user enters their resume into a text editor in the application. For example, the user enters the following text:

[0880] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[0881] Step 2: Submit your resume

[0882] Input: User-entered resume data

[0883] Output: Resume data sent to the server

[0884] Specific operation: The terminal sends the resume data entered by the user to the server using the HTTPS protocol. The JSON format for sending is as follows:

[0885] POST / api / submitResume HTTP / 1.1

[0886] Host: resume-advisor.example.com

[0887] Content-Type: application / json

[0888] {

[0889] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[0890] }

[0891] Step 3: Analyze resume data

[0892] Input: Resume data sent to the server

[0893] Output: Generates analysis results AI model input data

[0894] Specific operation: The server analyzes the text of the received resume. This analysis is performed using OpenAI's generative AI model, GPT-3. The server sends the following prompt to GPT-3:

[0895] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[0896] Step 4: Generate correction suggestions

[0897] Input: Analysis results from a generative AI model

[0898] Output: Proposed correction data

[0899] Specific operation: The server generates correction suggestions based on the analysis results of GPT-3. These correction suggestions include new wording suggestions, phrase corrections, and sentence restructuring. For example, the following correction suggestions are generated:

[0900] Current position: Project Manager (5 years)

[0901] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0902] Step 5: Submit your proposed revision

[0903] Input: Proposed correction data

[0904] Output: Suggested correction data sent to the user's device

[0905] Specific operation: The server sends the generated revision suggestions to the user's device, after which the user can revise their resume based on the suggestions.

[0906] Step 6: User revises resume

[0907] Input: Suggested correction data sent to the user's device

[0908] Output: Corrected resume data

[0909] Specific operation: The user checks the suggestions from the server and modifies his / her resume. For example, he / she modifies his / her resume based on the suggestions as follows:

[0910] Current position: Project Manager (5 years)

[0911] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[0912] Step 7: Resubmit your revised resume

[0913] Input: Revised resume data

[0914] Output: Resent resume data

[0915] Specific operation: The device sends the corrected resume data to the server again, again using the HTTPS protocol.

[0916] Step 8: Reassess your resume

[0917] Input: Resent resume data

[0918] Output: Secondary correction suggestions or evaluation data showing that no improvement is necessary

[0919] Specific behavior: The server re-analyzes the revised resume and either generates revision suggestions again or evaluates it as not requiring revision.

[0920] Step 9: Provide the best job offers

[0921] Input: Revised resume data and user registration information

[0922] Output: Optimal job posting data

[0923] Specific operation: The server will suggest the most suitable job information based on the user's revised resume and registered information. For example, the following job information will be generated.

[0924] Company Name: Technology Company

[0925] Job title: Project Manager

[0926] Location: Tokyo

[0927] Description: Responsible for managing large scale projects and customer relations.

[0928] This allows users to efficiently improve their resumes and find the best job opportunities.

[0929] (Application example 1)

[0930] 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."

[0931] In recent years, job seekers have been required to accurately and effectively describe their career history, but there is a lack of easy ways to do so. In particular, there is a need for a method that allows busy users, especially those in the midst of a job search, to create high-quality resumes without spending a lot of time. Furthermore, in order to quickly obtain appropriate job information, an advanced system that can perform detailed analysis of the user's career history and preferences is required. A new system that can solve these issues and improve user convenience is needed.

[0932] 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.

[0933] In this invention, the server includes means for a user to input their own resume, means for transmitting the resume to the server, means for the server to analyze the text of the resume, means for generating revision suggestions based on the analysis results, means for transmitting the revision suggestions to the user, means for the user to revise their resume based on the revision suggestions, means for converting voice input into text, and means for displaying the analysis results on the smart glasses. This allows the user to create a resume by voice input and further revise it while receiving feedback through the smart glasses, allowing them to easily and quickly obtain optimal job information.

[0934] "User" refers to an individual who uses the system to input or modify their resume.

[0935] A "resume" is a document that lists a user's work history, skills, career history, etc.

[0936] "Server" refers to a computer system that receives and analyzes data sent by users, and generates and returns suggested modifications.

[0937] "Voice input" is a method in which a user inputs information using voice.

[0938] "Text conversion" is the process of converting voice-input data into text form.

[0939] "Analysis means" refers to the function by which the server analyzes the resume, evaluates its contents, and identifies areas for improvement.

[0940] "Suggested revisions" refers to suggestions for improvements to the resume or new wording that the server provides to the user based on the analysis results.

[0941] "Smart glasses" are wearable devices that can visually display revision suggestions and other information to the user.

[0942] The present invention provides a system for users to efficiently improve their resumes. This system includes a series of processes, including voice input, text conversion, analysis, suggested revisions, feedback using smart glasses, and suggestion of optimal job information. An embodiment of this system will be described in detail below.

[0943] Voice to text conversion

[0944] The user uses the smart glasses to input voice data. For example, the user might say, "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met." This voice data is converted into text using the Google Speech-to-Text API.

[0945] Submit your resume

[0946] The device then uses the HTTPS protocol to transmit the converted text data to a server that uses the SSL / TLS protocol to ensure a secure connection.

[0947] Data analysis

[0948] The server analyzes the received resume text data using a generative AI model (GPT-3). The following prompt sentence is used for the analysis:

[0949] "Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years. I listened to client requests, managed project progress, and ensured deadlines were met."

[0950] Generation of correction suggestions and feedback

[0951] The server generates correction suggestions based on the results of GPT-3 analysis. For example, these correction suggestions may look like this:

[0952] Current position: Project Manager (5 years) Responsibilities: Understand customer requirements, manage project progress and ensure delivery deadlines.

[0953] The generated revision suggestions are visually fed back to the user through the smart glasses, allowing the user to review them and revise their resume.

[0954] Providing job information

[0955] The server generates optimal job information based on the user's revised resume and registered data (career history, skills, desired job type). For example, it provides the following job information:

[0956] "Company: IT Company B Position: Project Manager Location: Tokyo Description: Responsible for managing large-scale projects and dealing with customers."

[0957] This job information is visually displayed to the user using the smart glasses, allowing the user to select jobs that interest them and proceed with the application process.

[0958] In this way, the present invention allows users to effortlessly improve their resumes and quickly obtain the most suitable job information.

[0959] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0960] Step 1:

[0961] The user inputs voice data through the smart glasses. For example, the user might say, "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured delivery deadlines were met." This input voice data is captured by a microphone built into the smart glasses.

[0962] Step 2:

[0963] The device (smart glasses) converts the input voice data into text. To do this, the device calls the Google Speech-to-Text API to convert the voice data into text format. The input is the captured voice data, and the output is the text data corresponding to the voice content.

[0964] Step 3:

[0965] The terminal sends text data to the server using the HTTPS protocol to ensure confidentiality and integrity of the data. The input is the text data converted from the voice, and the output is a response confirming the data sent to the server.

[0966] Step 4:

[0967] The server analyzes the received text data. A generative AI model (GPT-3) is used for this analysis. Specifically, the server provides the text data to GPT-3 using the following prompt: "Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met." The input is the received text data, and the output is the correction suggestions generated by the analysis.

[0968] Step 5:

[0969] The server sends the generated correction suggestions back to the device. This transmission is also done using the HTTPS protocol. The input is the analysis result by GPT-3, i.e., the correction suggestions, and the output is the correction suggestions data sent to the device.

[0970] Step 6:

[0971] The terminal displays the suggested revisions on the display of the smart glasses. The user checks this visual feedback and revises the resume content as necessary. The input is the suggested revision data received from the server, and the output is the suggested revisions displayed on the display of the smart glasses.

[0972] Step 7:

[0973] The user corrects the resume based on the suggested corrections and sends it back to the server. The input is the resume text corrected by the user, and the output is the corrected data sent to the server.

[0974] Step 8:

[0975] The server generates optimal job listings based on the user's revised resume and registered data (career history, skills, desired job type). This is done using GPT-3 again. The input is the user's revised resume and registered information, and the output is the generated job listing.

[0976] Step 9:

[0977] The server sends the generated job information to the terminal, and the terminal displays the job information on the display of the smart glasses. The input is the generated job information, and the output is the job information visually displayed on the display of the smart glasses.

[0978] In this way, the present invention allows users to effortlessly improve their resumes and quickly obtain the most suitable job information.

[0979] 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.

[0980] The present invention provides a system that allows job seekers to input their resumes and efficiently improve them, and further combines it with an emotion engine that recognizes the user's emotions. This system transmits the resume entered by the user to a server, which analyzes its contents and generates revision suggestions. The system includes a process in which the user revises the resume based on the suggestions, and the server then suggests optimal job information. Furthermore, the emotion engine recognizes the user's emotions and reflects them in the revision suggestions, providing more appropriate support.

[0981] System Overview

[0982] Enter your resume

[0983] User:

[0984] A user enters their resume into a text editor in the application. For example, user A enters the following:

[0985] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[0986] Sending data

[0987] Device:

[0988] The resume data entered by the user is sent to the server. The HTTPS protocol is used to ensure a secure connection. For example, the following JSON data is sent:

[0989] POST / api / submitResume HTTP / 1.1

[0990] Host: resume-advisor.example.com

[0991] Content-Type: application / json

[0992] {

[0993] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[0994] }

[0995] Data analysis

[0996] server:

[0997] The server analyzes the received resume text data. First, the server converts the received data from JSON format to text data for analysis.

[0998] Next, we use GPT-3, a generative AI model, to evaluate the grammar and structure of the resume. For example, we give GPT-3 the following input to analyze it:

[0999] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[1000] Generate correction suggestions

[1001] server:

[1002] The server generates revision suggestions for the user's resume based on the results of GPT-3 analysis. These revision suggestions include new wording suggestions, corrected phrases, and restructured sentences. For example, it generates the following revision suggestions:

[1003] Current position: Project Manager (5 years)

[1004] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1005] Emotion recognition by emotion engine

[1006] Emotion Engine:

[1007] The emotion engine analyzes emotions based on user input and operational context, for example, analyzing how users react to suggested edits (e.g., frustration, joy, confusion) in real time.

[1008] Adjusting proposed changes

[1009] server:

[1010] The server adjusts the tone and content of the correction suggestions based on the output of the emotion engine. For example, if the user is feeling stressed, it will take a softer approach to the suggestions.

[1011] Below is an example of an adjustment suggested by the emotion engine.

[1012] Current position: Project Manager (5 years)

[1013] Responsibilities: I was responsible for properly understanding the client's requirements, managing the project progress smoothly, and ensuring delivery deadlines were met.

[1014] Submit and review your proposal

[1015] server:

[1016] The generated correction suggestions are sent to the user's device in JSON format.

[1017] HTTP / 1.1 200 OK

[1018] Content-Type: application / json

[1019] {

[1020] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[1021] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[1022] }

[1023] User:

[1024] The user checks the suggestions from the server and corrects his / her resume. For example, he / she makes the following corrections according to the suggestions.

[1025] Current position: Project Manager (5 years)

[1026] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1027] Submit new data and reassess

[1028] Device:

[1029] The corrected resume data is sent to the server again.

[1030] POST / api / submitResume HTTP / 1.1

[1031] Host: resume-advisor.example.com

[1032] Content-Type: application / json

[1033] {

[1034] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[1035] }

[1036] server:

[1037] Re-analyze the received revised resume and evaluate whether there are any further improvements. If necessary, generate and send another revision proposal.

[1038] Providing job information

[1039] server:

[1040] The user enters data to register their career history, skills, and desired job type. For example, User A registers the following data.

[1041] {

[1042] "career": "5 years of experience as a project manager",

[1043] "skills": "Project management, customer relations, delivery management",

[1044] "desiredPosition": "Project Manager"

[1045] }

[1046] server:

[1047] The server analyzes the user's career history, skills, and desired job type, and proposes the most suitable job information. For example, it generates the following job information:

[1048] {

[1049] "jobSuggestions": [

[1050] {

[1051] "company": "IT company B",

[1052] "position": "Project Manager",

[1053] "location": "Tokyo",

[1054] "description": "Responsible for managing large projects and customer relations."

[1055] }

[1056] ]

[1057] }

[1058] Device:

[1059] The proposed job listings are displayed to the user, who can then select the job that interests them and proceed with the application process.

[1060] The processing flow will be explained below.

[1061] Step 1:

[1062] A user enters a resume into a text editor within the application. For example, the user enters the following text:

[1063] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[1064] Step 2:

[1065] The terminal sends the resume data entered by the user to the server. The HTTPS protocol is used to ensure a secure connection. For example, the following JSON data is sent:

[1066] POST / api / submitResume HTTP / 1.1

[1067] Host: resume-advisor.example.com

[1068] Content-Type: application / json

[1069] {

[1070] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[1071] }

[1072] Step 3:

[1073] The server analyzes the text data of the resume it receives. First, the server converts the received data from JSON format to text data for analysis.

[1074] Step 4:

[1075] The server uses the generative AI model GPT-3 to evaluate the grammar and structure of the resume. For example, it gives prompts like the following to GPT-3:

[1076] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[1077] Step 5:

[1078] The server generates revision suggestions for the user's resume based on the GPT-3 response. These revision suggestions include new wording suggestions, phrase corrections, and sentence restructuring. For example, the following revision suggestions are generated:

[1079] Current position: Project Manager (5 years)

[1080] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1081] Step 6:

[1082] The emotion engine analyzes emotions based on the user's input and operational status. For example, it analyzes in real time whether the user is feeling stressed about the suggested corrections.

[1083] Step 7:

[1084] The server adjusts the tone and content of the correction suggestions based on the output of the emotion engine. For example, if the user is feeling stressed, it will adopt a softer tone approach. Below is an example of an adjusted correction suggestion.

[1085] Current position: Project Manager (5 years)

[1086] Responsibilities: I was responsible for properly understanding the client's requirements, managing the project progress smoothly, and ensuring delivery deadlines were met.

[1087] Step 8:

[1088] The server generates correction suggestions and sends them to the user's device in JSON format.

[1089] HTTP / 1.1 200 OK

[1090] Content-Type: application / json

[1091] {

[1092] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[1093] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[1094] }

[1095] Step 9:

[1096] The user checks the suggestions from the server and corrects the resume. For example, the user corrects the resume as follows according to the suggestions.

[1097] Current position: Project Manager (5 years)

[1098] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1099] Step 10:

[1100] The terminal transmits the corrected resume data to the server again.

[1101] POST / api / submitResume HTTP / 1.1

[1102] Host: resume-advisor.example.com

[1103] Content-Type: application / json

[1104] {

[1105] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[1106] }

[1107] Step 11:

[1108] The server re-analyzes the received revised resume and evaluates whether there are any further improvements, and if necessary, generates and sends another revision proposal.

[1109] Step 12:

[1110] The user enters data to register their career history, skills, and desired job type. For example, User A registers the following data.

[1111] {

[1112] "career": "5 years of experience as a project manager",

[1113] "skills": "Project management, customer relations, delivery management",

[1114] "desiredPosition": "Project Manager"

[1115] }

[1116] Step 13:

[1117] The server analyzes the user's career history, skills, and desired job type, and proposes the most suitable job information. For example, it generates the following job information:

[1118] {

[1119] "jobSuggestions": [

[1120] {

[1121] "company": "IT company",

[1122] "position": "Project Manager",

[1123] "location": "Tokyo",

[1124] "description": "Responsible for managing large projects and customer relations."

[1125] }

[1126] ]

[1127] }

[1128] Step 14:

[1129] The device displays the suggested job listings to the user, who can then select the job that interests them and proceed with the application process.

[1130] Example 2

[1131] 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."

[1132] Conventional resume creation support systems lack the functionality to automatically correct and optimize the content entered by the user, and do not provide support that takes the user's emotions into consideration. This can cause users to feel stressed. Furthermore, the lack of a function to suggest optimal job opportunities poses a challenge, making job searches less efficient.

[1133] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1134] In this invention, the server includes: means for a user to input their resume; means for transmitting the resume to the server; means for the server to analyze the text of the resume; means for generating revision suggestions based on the analysis results using a generative AI model; means including an emotion recognition engine that recognizes the user's emotions; means for adjusting the revision suggestions based on the output of the emotion recognition engine; means for transmitting the revision suggestions to the user; and means for the user to revise their resume based on the revision suggestions. This makes it possible to efficiently revise and optimize the user's resume, provide support that takes the user's emotions into consideration, and further, by suggesting optimal employment opportunities, enable efficient job hunting.

[1135] "User" refers to an individual who enters a resume and receives suggested revisions.

[1136] "Terminal" refers to an electronic device that allows a user to input a resume and transmit and receive data to and from a server.

[1137] "Server" refers to the computer system that analyzes resumes, generates revision suggestions, recognizes emotions, and makes job suggestions.

[1138] A "resume" refers to a document that lists a user's work history, skills, responsibilities, etc.

[1139] "Generative AI model" refers to the artificial intelligence algorithm used to analyze the content of a resume and generate suggested revisions.

[1140] An "emotion recognition engine" refers to a system that analyzes a user's emotions in real time and uses them to adjust suggested corrections.

[1141] "Suggested revisions" refers to the revisions the generative AI model suggests for improvement after evaluating the grammar and structure of the resume.

[1142] "Job information" refers to information about job opportunities suggested based on the user's career history, skills, and desired job type.

[1143] "Analysis" refers to the process of breaking down the content of a resume and evaluating its grammar and structure.

[1144] "Secure Connection" means an encrypted network connection for secure data communication.

[1145] The present invention relates to a system for efficiently improving a resume and providing support that takes into account the user's feelings. Specifically, the system involves a series of processes: inputting a user's resume, analyzing it, generating revision suggestions, and suggesting optimal job information.

[1146] To implement this system, the following hardware and software are used.

[1147] Hardware and software used

[1148] 1. Terminal: An electronic device on which a user inputs their resume and sends and receives data to and from the server. Examples include a PC or smartphone.

[1149] 2. Server: A computer system that analyzes resumes, generates revision suggestions, recognizes emotions, and proposes job information. The server is equipped with a high-performance CPU and large-capacity memory, and is installed with a database management system and an AI model operation environment.

[1150] 3. Generative AI model: An artificial intelligence algorithm used to analyze resume content and generate revision suggestions. A specific example is GPT-3 (Generative Pre-trained Transformer 3).

[1151] 4. Emotion Recognition Engine: A system that analyzes user emotions in real time and uses them to adjust revision suggestions. Software that implements specific emotion recognition algorithms is required.

[1152] Example of a system

[1153] Enter your resume

[1154] User: Enter their resume details into the text editor within the application. For example, enter the following:

[1155] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[1156] Sending data

[1157] Terminal: The resume data entered by the user is sent to the server, using the HTTPS protocol to ensure a secure connection.

[1158] Data analysis

[1159] Server: To analyze the received resume text data, the server converts the received data from JSON format to text data for analysis. Next, it uses the generative AI model GPT-3 to evaluate the grammar and structure. For example, it provides the following prompt sentence to GPT-3:

[1160] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[1161] Generate correction suggestions

[1162] Server: Based on the results of GPT-3 analysis, the server generates suggested revisions to the resume. For example, this includes suggesting new wording, correcting phrases, and restructuring sentences. Specific examples of suggested revisions include:

[1163] Current position: Project Manager (5 years)

[1164] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1165] Emotion recognition using an emotion recognition engine

[1166] Emotion Recognition Engine: Analyzes the user's reactions to suggested revisions. The emotion recognition engine recognizes the user's emotions, such as frustration, joy, and confusion, in real time.

[1167] Adjusting proposed changes

[1168] Server: Based on the output of the emotion recognition engine, the tone and content of the correction suggestions are adjusted. For example, if the user is feeling stressed, the suggestion is softened by the following:

[1169] Current position: Project Manager (5 years)

[1170] Responsibilities: I was responsible for properly understanding the client's requirements, managing the project progress smoothly, and ensuring delivery deadlines were met.

[1171] Submit and review your proposal

[1172] Server: The generated revision suggestions are sent in JSON format to the user's device. The user checks the revision suggestions from the server and revise their resume based on them.

[1173] In this way, the system of the present invention allows users to efficiently improve their resumes and obtain optimal job information while receiving appropriate support using emotion recognition.

[1174] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1175] Step 1: Enter your resume

[1176] User: Enter your resume into the text editor within the application. For example, enter the following:

[1177] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[1178] Input: The action of a user typing their resume into a text editor.

[1179] Output: The resume text saved in a text editor.

[1180] Step 2: Sending data

[1181] Terminal: The text data of the entered resume is sent to the server using the HTTPS protocol to ensure a secure connection.

[1182] json

[1183] POST / api / submitResume HTTP / 1.1

[1184] Host: resume-advisor.example.com

[1185] Content-Type: application / json

[1186] {

[1187] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[1188] }

[1189] Input: Resume data in a text editor.

[1190] Output: Text data of the submitted resume.

[1191] Step 3: Analyze the data

[1192] Server: Converts the received resume text data from JSON format to text data for analysis. Next, it uses the generative AI model GPT-3 to evaluate grammar and structure.

[1193] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[1194] Input: JSON data of the submitted resume.

[1195] Output: Analysis results by GPT-3.

[1196] Step 4: Generate correction suggestions

[1197] Server: Generates correction suggestions based on the results of GPT-3 analysis, such as proposing new wording or restructuring sentences.

[1198] Current position: Project Manager (5 years)

[1199] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1200] Input: Analysis results by GPT-3.

[1201] Output: Text data of suggested corrections.

[1202] Step 5: Emotion recognition by the emotion recognition engine

[1203] Emotion recognition engine: Analyzes emotions based on user input and operation status. For example, it analyzes how users react to suggested corrections (e.g., irritation, joy, confusion) in real time.

[1204] Input: User response data.

[1205] Output: User sentiment analysis results.

[1206] Step 6: Adjust the proposed changes

[1207] Server: Based on the output of the emotion recognition engine, the tone and content of the correction suggestions are adjusted. For example, if the user is feeling stressed, the tone of the suggestions is softened.

[1208] Current position: Project Manager (5 years)

[1209] Responsibilities: I was responsible for properly understanding the client's requirements, managing the project progress smoothly, and ensuring delivery deadlines were met.

[1210] Input: User sentiment analysis results, initial correction suggestions.

[1211] Output: Text data with sentiment-sensitive revision suggestions.

[1212] Step 7: Submit and review your proposal

[1213] Server: The generated correction suggestions are sent to the user's device in JSON format.

[1214] json

[1215] HTTP / 1.1 200 OK

[1216] Content-Type: application / json

[1217] {

[1218] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[1219] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[1220] }

[1221] User: Check the suggested revisions from the server and revise the resume based on them.

[1222] Current position: Project Manager (5 years)

[1223] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1224] Input: Emotion-sensitive revision suggestions.

[1225] Output: The corrected resume text data.

[1226] Step 8: Submit new data and reassess

[1227] Terminal: Send the corrected resume data to the server again.

[1228] json

[1229] POST / api / submitResume HTTP / 1.1

[1230] Host: resume-advisor.example.com

[1231] Content-Type: application / json

[1232] {

[1233] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[1234] }

[1235] Server: Re-analyzes the resubmitted revised resume and evaluates whether there are any further improvements needed. If necessary, generates revision suggestions again and sends them to the user.

[1236] Input: Text data of the revised resume.

[1237] Output: Text data of the final revision suggestions.

[1238] Step 9: Post a job offer

[1239] Server: Analyzes the data registered by users regarding their career history, skills, and desired job type, and proposes the most suitable job information. For example, it generates the following job information:

[1240] json

[1241] {

[1242] "jobSuggestions": [

[1243] {

[1244] "company": "IT company",

[1245] "position": "Project Manager",

[1246] "location": "Tokyo",

[1247] "description": "Responsible for managing large projects and customer relations."

[1248] }

[1249] ]

[1250] }

[1251] Input: User's background, skills, and desired job data.

[1252] Output: Data suggesting the best job listings.

[1253] Terminal: Displays suggested job information to the user, who can then select the job they are interested in and proceed with the application process.

[1254] (Application example 2)

[1255] 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."

[1256] In today's world, people are expected to be able to effectively express their thoughts and opinions and communicate better with others. However, opinions are often not conveyed properly due to individual expressiveness and emotional influences. In addition, when a user receives necessary suggestions or feedback, it is necessary to appropriately adjust the suggestions based on the detected user's emotions. Therefore, this invention aims to provide a system that supports more appropriate and effective communication by analyzing users' opinions and impressions in real time, improving the content, and utilizing an emotion engine to suggest modifications that match the user's emotions.

[1257] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to input their own information, means for transmitting the information to the server, means for the server to analyze the text of the information, means for generating a revision suggestion based on the analysis result, means for transmitting the revision suggestion to the user, means for the user to correct their information based on the revision suggestion, and means for recognizing the user's emotions using an emotion engine and adjusting the revision suggestion. This allows the user to effectively improve their own information while receiving suggestions that take their emotions into consideration, thereby improving the quality of self-expression and communication.

[1258] "User" refers to an individual who enters their information and uses the system.

[1259] "Information" refers to opinions, impressions, or other written content entered by the user.

[1260] A "server" is a computer system that receives and analyzes user-submitted information, and generates and transmits revision suggestions.

[1261] "Parsing" is the process of evaluating the grammar, structure, and content of user-entered information and generating appropriate correction suggestions.

[1262] "Suggested corrections" are suggestions for improving the information entered by the user, including new wording suggestions, corrected phrases, and restructured sentences.

[1263] An "emotion engine" is software or hardware that recognizes and analyzes a user's emotions.

[1264] "Adjusting" refers to appropriately changing the tone and content of the revision suggestion depending on the user's emotion as recognized by the emotion engine.

[1265] This invention is a system that allows users to input their own information (opinions, impressions, etc.) and efficiently improve it. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides more appropriate support.

[1266] System Overview

[1267] Enter and submit information

[1268] A user inputs their information into a text editor via a device such as a smartphone or smart glasses. For example, a user inputs their review of a movie as follows:

[1269] "This movie was moving, but I wish the climax had been a little more impressive."

[1270] The information entered by the user is sent to the server via a secure protocol (e.g., HTTPS).

[1271] Analysis of information

[1272] The server analyzes the received information. First, it converts the received data into text data, and then uses a generative AI model (e.g., GPT-3) to evaluate the grammar and structure of the information. For example, it analyzes the information by giving GPT-3 the following prompt sentence:

[1273] "Please make your comments more professional and concise: The film was moving, but I wish the climax was a little more impactful."

[1274] Generate correction suggestions

[1275] Based on the analysis results, the server will suggest how to correct the user's information. The suggested corrections include new wording, corrected phrases, and restructured sentences. For example, the server will generate the following correction suggestions:

[1276] "The film was very moving, but I thought there was room for an even stronger climax."

[1277] Emotion recognition and regulation with emotion engine

[1278] Emotion engines (e.g., EmoReact) analyze user emotions based on their input and operational context. For example, if a user is frustrated, the tone of the suggested corrections will be softened. Below is an example of an adjustment made by an emotion engine.

[1279] "The film was very moving, but I thought there was room for the climax to be even more impactful. I agree with you."

[1280] Submit and review your proposal

[1281] The server sends the generated revision suggestions to the user, who then confirms and corrects them.

[1282] Hardware and software used

[1283] Hardware: Smartphones, smart glasses, servers.

[1284] Software: GPT-3 (generative AI model), EmoReact (emotion engine), secure data transmission via HTTPS protocol.

[1285] A concrete example of a prompt from a generative AI model

[1286] 1. Prompts to improve your opinion:

[1287] "Please make your comments more professional and concise: The film was moving, but I wish the climax was a little more impactful."

[1288] 2. Emotion-awareness regulation reflection prompt:

[1289] "Please tone it down if the user is stressed: This movie was moving, but I wish the climax was a little more impactful. I agree with you."

[1290] In this way, users can effectively improve their information and receive appropriate emotional support.

[1291] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1292] Step 1:

[1293] A user inputs their information through a text editor on a smartphone or smart glasses. For example, a user may write their impression of a movie as, "This movie was moving, but I wish the climax had been more memorable."

[1294] input:

[1295] Text data of user opinions and impressions.

[1296] output:

[1297] The entered information is stored on the terminal and is ready to be sent to the next processing step.

[1298] Step 2:

[1299] The device securely transmits the entered information to the server using the HTTPS protocol, and the transmitted data is packaged in JSON format.

[1300] input:

[1301] Text data entered by the user.

[1302] output:

[1303] Text data sent to a server over a secure protocol.

[1304] Specific behavior:

[1305] The terminal converts the user's text data into JSON format and sends it to the server using the HTTPS protocol.

[1306] Step 3:

[1307] The server converts the received text data into text for analysis and feeds it to a generative AI model (e.g., GPT-3) to evaluate grammar and composition. For example, it uses a prompt sentence such as, "Please make the provided opinion more professional and concise: This movie was moving, but I think the climax could have been more impressive."

[1308] input:

[1309] Text data received in JSON format.

[1310] output:

[1311] Analysis results (correction suggestions) generated by the generative AI model.

[1312] Specific behavior:

[1313] The server extracts text from the JSON data and inputs it to GPT-3 along with a prompt sentence for analysis.

[1314] Step 4:

[1315] The server generates suggestions for correcting the user's information based on the analysis, including new wording, corrected phrases, and restructured sentences.

[1316] input:

[1317] Text data analyzed by a generative AI model.

[1318] output:

[1319] Text data of the proposed correction.

[1320] Specific behavior:

[1321] Based on the analysis results, the server generates text that suggests new phrases, corrections to phrases, and restructuring of sentences.

[1322] Step 5:

[1323] The server uses an emotion engine (e.g., EmoReact) to recognize the user's emotions in real time and adjust the tone and content of the correction suggestions accordingly, for example, to tone down the suggestion if the user is annoyed.

[1324] input:

[1325] Emotional data based on user input and operation status.

[1326] output:

[1327] Text data with sentiment-adjusted revision suggestions.

[1328] Specific behavior:

[1329] The server uses emotion recognition software to analyze the user's emotions and adjusts the tone and content of the revision suggestions based on the results.

[1330] Step 6:

[1331] The server then sends the generated correction suggestions to the user's device via a secure protocol, packaged in JSON format.

[1332] input:

[1333] Text data of the adjusted correction proposal.

[1334] output:

[1335] The suggested fixes sent to the user's device.

[1336] Specific behavior:

[1337] The server converts the proposed revisions into JSON format and sends them to the terminal using the HTTPS protocol.

[1338] Step 7:

[1339] The user checks the received correction suggestions and corrects his / her information. Based on the correction suggestions, the user updates the information.

[1340] input:

[1341] Text data of the suggested revision sent from the server.

[1342] output:

[1343] The text data of the corrected information.

[1344] Specific behavior:

[1345] The user reviews the received revision suggestions and updates the information by applying new wording, correcting phrases, and restructuring the sentence.

[1346] 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.

[1347] 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.

[1348] 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.

[1349] [Third embodiment]

[1350] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1351] 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.

[1352] 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).

[1353] 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.

[1354] 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.

[1355] 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).

[1356] 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.

[1357] 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.

[1358] 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.

[1359] 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.

[1360] 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.

[1361] 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."

[1362] The present invention is a system that allows job seekers to input their resumes and improve them efficiently. This system involves sending the resumes entered by users to a server, which analyzes the contents and generates suggestions for revision. The user then revises the resume based on the suggestions, and the server then suggests the most suitable job information.

[1363] System Overview

[1364] Enter your resume

[1365] User:

[1366] A user enters their resume into a text editor in the application. For example, user A enters the following:

[1367] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[1368] Sending data

[1369] Device:

[1370] The resume data entered by the user is sent to the server using the HTTPS protocol to ensure a secure connection.

[1371] POST / api / submitResume HTTP / 1.1

[1372] Host: resume-advisor.example.com

[1373] Content-Type: application / json

[1374] {

[1375] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[1376] }

[1377] Data analysis

[1378] server:

[1379] The server analyzes the text of the received resume and utilizes the generative AI model GPT-3 to evaluate grammar and structure.

[1380] For example, the following input is given to GPT-3 for analysis:

[1381] GPT-3: Rewrite the following resume section to be more professional and concise: I worked as a project manager for 5 years, listening to client requests, managing project progress and ensuring deadlines are met.

[1382] Generate correction suggestions

[1383] server:

[1384] The server generates revision suggestions for the user's resume based on the results of GPT-3 analysis. These revision suggestions include new wording suggestions, corrected phrases, and restructured sentences. For example, it generates the following revision suggestions:

[1385] Current position: Project Manager (5 years)

[1386] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1387] Submit and review your proposal

[1388] server:

[1389] The generated revision suggestions are sent to the user's terminal.

[1390] HTTP / 1.1 200 OK

[1391] Content-Type: application / json

[1392] {

[1393] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[1394] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[1395] }

[1396] User:

[1397] The user checks the suggestions from the server and corrects his / her resume. For example, he / she makes the following corrections according to the suggestions.

[1398] Current position: Project Manager (5 years)

[1399] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1400] Submit new data and reassess

[1401] Device:

[1402] The corrected resume data is sent to the server again.

[1403] POST / api / submitResume HTTP / 1.1

[1404] Host: resume-advisor.example.com

[1405] Content-Type: application / json

[1406] {

[1407] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[1408] }

[1409] server:

[1410] Re-analyze the received revised resume and evaluate whether there are any further improvements. If necessary, generate and send another revision proposal.

[1411] Providing job information

[1412] server:

[1413] The system analyzes the data registered by users about their career history, skills, and desired job type, and suggests the most suitable job information. For example, it generates the following job information:

[1414] json

[1415] {

[1416] "jobSuggestions": [

[1417] {

[1418] "company": "IT company B",

[1419] "position": "Project Manager",

[1420] "location": "Tokyo",

[1421] "description": "Responsible for managing large projects and customer relations."

[1422] }

[1423] ]

[1424] }

[1425] Device:

[1426] The proposed job listings are displayed to the user, who can then select the job that interests them and proceed with the application process.

[1427] The processing flow will be explained below.

[1428] Step 1:

[1429] A user enters a resume into a text editor within the application. For example, the user enters the following text:

[1430] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[1431] Step 2:

[1432] The terminal sends the resume data entered by the user to the server. The HTTPS protocol is used to ensure a secure connection. For example, the following JSON data is sent:

[1433] POST / api / submitResume HTTP / 1.1

[1434] Host: resume-advisor.example.com

[1435] Content-Type: application / json

[1436] {

[1437] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[1438] }

[1439] Step 3:

[1440] The server analyzes the text data of the resume it receives. First, the server converts the received data from JSON format to text data for analysis.

[1441] Step 4:

[1442] The server uses the generative AI model GPT-3 to evaluate the grammar and structure of the resume, providing prompts like the following to GPT-3:

[1443] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[1444] Step 5:

[1445] The server then uses the GPT-3 results to generate suggested revisions to the user's resume, including new wording suggestions, corrected phrases, and restructured sentences.

[1446] Current position: Project Manager (5 years)

[1447] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1448] Step 6:

[1449] The server generates correction suggestions and sends them to the user's device in JSON format.

[1450] HTTP / 1.1 200 OK

[1451] Content-Type: application / json

[1452] {

[1453] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[1454] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[1455] }

[1456] Step 7:

[1457] The user checks the suggestions from the server and corrects his / her resume. The user makes the following corrections according to the suggestions.

[1458] Current position: Project Manager (5 years)

[1459] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1460] Step 8:

[1461] The terminal transmits the corrected resume data to the server again.

[1462] POST / api / submitResume HTTP / 1.1

[1463] Host: resume-advisor.example.com

[1464] Content-Type: application / json

[1465] {

[1466] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[1467] }

[1468] Step 9:

[1469] The server re-analyzes the received revised resume and evaluates whether there are any further improvements, and if necessary, generates and sends another revision proposal.

[1470] Step 10:

[1471] The user enters data to register their career history, skills, and desired job type. For example, User A registers the following data.

[1472] {

[1473] "career": "5 years of experience as a project manager",

[1474] "skills": "Project management, customer relations, delivery management",

[1475] "desiredPosition": "Project Manager"

[1476] }

[1477] Step 11:

[1478] The server analyzes the user's career history, skills, and desired job type, and proposes the most suitable job information. For example, it generates the following job information:

[1479] {

[1480] "jobSuggestions": [

[1481] {

[1482] "company": "IT company B",

[1483] "position": "Project Manager",

[1484] "location": "Tokyo",

[1485] "description": "Responsible for managing large projects and customer relations."

[1486] }

[1487] ]

[1488] }

[1489] Step 12:

[1490] The device displays the suggested job listings to the user, who can then select the job that interests them and proceed with the application process.

[1491] Example 1

[1492] 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."

[1493] Conventional resume creation systems require users to manually edit resumes, which is time-consuming and labor-intensive. Finding appropriate job postings also requires users' own efforts. Furthermore, applying for a job without reviewing grammar and structure can reduce the effectiveness of job searches. Therefore, there is a need for a system that can efficiently improve resumes and provide optimal job postings.

[1494] 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.

[1495] In this invention, the server includes a means for a user to input their own resume, a means for transmitting the resume to the server using a data transmission device, a means for the server to analyze the resume text using a generative AI model, a means for generating revision suggestions based on the analysis results, a means for transmitting the revision suggestions to the user's terminal, and a means for the user to revise their resume based on the revision suggestions. This allows the user to quickly and efficiently improve their resume and receive optimal job information.

[1496] "User" refers to the individual or entity that creates, inputs, or modifies a resume.

[1497] "Resume" refers to a document that lists a user's work history, skills, achievements, qualifications, etc.

[1498] The "data transmission device" refers to hardware or software for transmitting the resume entered by the user to the server.

[1499] "Server" refers to a central processing unit that receives user-submitted resumes, analyzes them, and generates revision suggestions.

[1500] "Generative AI model" refers to an artificial intelligence platform that uses natural language processing technology to analyze resume text and generate revision suggestions.

[1501] "Analysis" refers to the process of using a generative AI model to evaluate the grammar, structure, and content of a resume to identify areas for improvement.

[1502] "Suggested revisions" refers to the resume improvement suggestions provided by the generative AI model based on the analysis results.

[1503] "Device" refers to the device (e.g., computer, tablet, smartphone, etc.) through which a user enters their resume and receives suggested revisions.

[1504] "Best-fit job information" refers to information about job opportunities selected based on the user's resume and registration information.

[1505] MODE FOR CARRYING OUT THE INVENTION

[1506] The present invention is a system for enabling job seekers to efficiently improve their resumes, which involves a series of processes in which a user inputs their resume, sends the data to a server, and the server analyzes it, generates suggestions for revision, and provides feedback to the user.

[1507] Hardware and software used

[1508] Hardware:

[1509] Devices: Computers, tablets, smartphones, etc.

[1510] Server: A central processing unit that performs high-performance data processing.

[1511] software:

[1512] Program: A custom application for sending, receiving, parsing resume data, and generating revision suggestions.

[1513] Generative AI model: An artificial intelligence platform that uses natural language processing techniques such as OpenAI's GPT-3.

[1514] Specific operation of the system

[1515] User:

[1516] The user enters their resume into a text editor within the application, for example by entering the following:

[1517] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[1518] Device:

[1519] The terminal sends the entered resume to the server using the HTTPS protocol, with end-to-end encryption used during the transmission process to ensure data security.

[1520] server:

[1521] The server analyzes the text of the received resume. For this analysis, it uses the generative AI model GPT-3. The server starts the analysis by sending the following prompt to GPT-3:

[1522] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[1523] server:

[1524] Based on the analysis results of GPT-3, correction suggestions are generated. These correction suggestions include new wording suggestions, phrase corrections, and sentence restructuring. An example of a generated correction suggestion is as follows:

[1525] Current position: Project Manager (5 years)

[1526] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1527] server:

[1528] The generated revision suggestions are sent to the user's terminal, and feedback is provided for the user to re-revise their resume. The revised resume data is sent back to the server for re-evaluation.

[1529] server:

[1530] Finally, the app will suggest suitable job listings based on the user's resume and registered information, including details such as company name, position, location, and job description.

[1531] Specific examples

[1532] For example, if User A enters his / her resume and sends it with the following message, "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met," the server will analyze it using GPT-3, a generative AI model, and return the following suggested revisions to User A:

[1533] Current position: Project Manager (5 years)

[1534] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1535] User A then follows the suggestions to revise their resume and undergo further reevaluation to refine it to the best possible form. Ultimately, User A is presented with job information that best suits their background and skills, enabling them to efficiently search for a job.

[1536] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1537] Step 1: User enters resume

[1538] Input: User's resume text

[1539] Output: Input resume data

[1540] Specific behavior: A user enters their resume into a text editor in the application. For example, the user enters the following text:

[1541] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[1542] Step 2: Submit your resume

[1543] Input: User-entered resume data

[1544] Output: Resume data sent to the server

[1545] Specific operation: The terminal sends the resume data entered by the user to the server using the HTTPS protocol. The JSON format for sending is as follows:

[1546] POST / api / submitResume HTTP / 1.1

[1547] Host: resume-advisor.example.com

[1548] Content-Type: application / json

[1549] {

[1550] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[1551] }

[1552] Step 3: Analyze resume data

[1553] Input: Resume data sent to the server

[1554] Output: Generates analysis results AI model input data

[1555] Specific operation: The server analyzes the text of the received resume. This analysis is performed using OpenAI's generative AI model, GPT-3. The server sends the following prompt to GPT-3:

[1556] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[1557] Step 4: Generate correction suggestions

[1558] Input: Analysis results from a generative AI model

[1559] Output: Proposed correction data

[1560] Specific operation: The server generates correction suggestions based on the analysis results of GPT-3. These correction suggestions include new wording suggestions, phrase corrections, and sentence restructuring. For example, the following correction suggestions are generated:

[1561] Current position: Project Manager (5 years)

[1562] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1563] Step 5: Submit your proposed revision

[1564] Input: Proposed correction data

[1565] Output: Suggested correction data sent to the user's device

[1566] Specific operation: The server sends the generated revision suggestions to the user's device, after which the user can revise their resume based on the suggestions.

[1567] Step 6: User revises resume

[1568] Input: Suggested correction data sent to the user's device

[1569] Output: Corrected resume data

[1570] Specific operation: The user checks the suggestions from the server and modifies his / her resume. For example, he / she modifies his / her resume based on the suggestions as follows:

[1571] Current position: Project Manager (5 years)

[1572] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1573] Step 7: Resubmit your revised resume

[1574] Input: Revised resume data

[1575] Output: Resent resume data

[1576] Specific operation: The device sends the corrected resume data to the server again, again using the HTTPS protocol.

[1577] Step 8: Reassess your resume

[1578] Input: Resent resume data

[1579] Output: Secondary correction suggestions or evaluation data showing that no improvement is necessary

[1580] Specific behavior: The server re-analyzes the revised resume and either generates revision suggestions again or evaluates it as not requiring revision.

[1581] Step 9: Provide the best job offers

[1582] Input: Revised resume data and user registration information

[1583] Output: Optimal job posting data

[1584] Specific operation: The server will suggest the most suitable job information based on the user's revised resume and registered information. For example, the following job information will be generated.

[1585] Company Name: Technology Company

[1586] Job title: Project Manager

[1587] Location: Tokyo

[1588] Description: Responsible for managing large scale projects and customer relations.

[1589] This allows users to efficiently improve their resumes and find the best job opportunities.

[1590] (Application example 1)

[1591] 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."

[1592] In recent years, job seekers have been required to accurately and effectively describe their career history, but there is a lack of easy ways to do so. In particular, there is a need for a method that allows busy users, especially those in the midst of a job search, to create high-quality resumes without spending a lot of time. Furthermore, in order to quickly obtain appropriate job information, an advanced system that can perform detailed analysis of the user's career history and preferences is required. A new system that can solve these issues and improve user convenience is needed.

[1593] 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.

[1594] In this invention, the server includes means for a user to input their own resume, means for transmitting the resume to the server, means for the server to analyze the text of the resume, means for generating revision suggestions based on the analysis results, means for transmitting the revision suggestions to the user, means for the user to revise their resume based on the revision suggestions, means for converting voice input into text, and means for displaying the analysis results on the smart glasses. This allows the user to create a resume by voice input and further revise it while receiving feedback through the smart glasses, allowing them to easily and quickly obtain optimal job information.

[1595] "User" refers to an individual who uses the system to input or modify their resume.

[1596] A "resume" is a document that lists a user's work history, skills, career history, etc.

[1597] "Server" refers to a computer system that receives and analyzes data sent by users, and generates and returns suggested modifications.

[1598] "Voice input" is a method in which a user inputs information using voice.

[1599] "Text conversion" is the process of converting voice-input data into text form.

[1600] "Analysis means" refers to the function by which the server analyzes the resume, evaluates its contents, and identifies areas for improvement.

[1601] "Suggested revisions" refers to suggestions for improvements to the resume or new wording that the server provides to the user based on the analysis results.

[1602] "Smart glasses" are wearable devices that can visually display revision suggestions and other information to the user.

[1603] The present invention provides a system for users to efficiently improve their resumes. This system includes a series of processes, including voice input, text conversion, analysis, suggested revisions, feedback using smart glasses, and suggestion of optimal job information. An embodiment of this system will be described in detail below.

[1604] Voice to text conversion

[1605] The user uses the smart glasses to input voice data. For example, the user might say, "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met." This voice data is converted into text using the Google Speech-to-Text API.

[1606] Submit your resume

[1607] The device then uses the HTTPS protocol to transmit the converted text data to a server that uses the SSL / TLS protocol to ensure a secure connection.

[1608] Data analysis

[1609] The server analyzes the received resume text data using a generative AI model (GPT-3). The following prompt sentence is used for the analysis:

[1610] "Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years. I listened to client requests, managed project progress, and ensured deadlines were met."

[1611] Generation of correction suggestions and feedback

[1612] The server generates correction suggestions based on the results of GPT-3 analysis. For example, these correction suggestions may look like this:

[1613] Current position: Project Manager (5 years) Responsibilities: Understand customer requirements, manage project progress and ensure delivery deadlines.

[1614] The generated revision suggestions are visually fed back to the user through the smart glasses, allowing the user to review them and revise their resume.

[1615] Providing job information

[1616] The server generates optimal job information based on the user's revised resume and registered data (career history, skills, desired job type). For example, it provides the following job information:

[1617] "Company: IT Company B Position: Project Manager Location: Tokyo Description: Responsible for managing large-scale projects and dealing with customers."

[1618] This job information is visually displayed to the user using the smart glasses, allowing the user to select jobs that interest them and proceed with the application process.

[1619] In this way, the present invention allows users to effortlessly improve their resumes and quickly obtain the most suitable job information.

[1620] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1621] Step 1:

[1622] The user inputs voice data through the smart glasses. For example, the user might say, "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured delivery deadlines were met." This input voice data is captured by a microphone built into the smart glasses.

[1623] Step 2:

[1624] The device (smart glasses) converts the input voice data into text. To do this, the device calls the Google Speech-to-Text API to convert the voice data into text format. The input is the captured voice data, and the output is the text data corresponding to the voice content.

[1625] Step 3:

[1626] The terminal sends text data to the server using the HTTPS protocol to ensure confidentiality and integrity of the data. The input is the text data converted from the voice, and the output is a response confirming the data sent to the server.

[1627] Step 4:

[1628] The server analyzes the received text data. A generative AI model (GPT-3) is used for this analysis. Specifically, the server provides the text data to GPT-3 using the following prompt: "Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met." The input is the received text data, and the output is the correction suggestions generated by the analysis.

[1629] Step 5:

[1630] The server sends the generated correction suggestions back to the device. This transmission is also done using the HTTPS protocol. The input is the analysis result by GPT-3, i.e., the correction suggestions, and the output is the correction suggestions data sent to the device.

[1631] Step 6:

[1632] The terminal displays the suggested revisions on the display of the smart glasses. The user checks this visual feedback and revises the resume content as necessary. The input is the suggested revision data received from the server, and the output is the suggested revisions displayed on the display of the smart glasses.

[1633] Step 7:

[1634] The user corrects the resume based on the suggested corrections and sends it back to the server. The input is the resume text corrected by the user, and the output is the corrected data sent to the server.

[1635] Step 8:

[1636] The server generates optimal job listings based on the user's revised resume and registered data (career history, skills, desired job type). This is done using GPT-3 again. The input is the user's revised resume and registered information, and the output is the generated job listing.

[1637] Step 9:

[1638] The server sends the generated job information to the terminal, and the terminal displays the job information on the display of the smart glasses. The input is the generated job information, and the output is the job information visually displayed on the display of the smart glasses.

[1639] In this way, the present invention allows users to effortlessly improve their resumes and quickly obtain the most suitable job information.

[1640] 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.

[1641] The present invention provides a system that allows job seekers to input their resumes and efficiently improve them, and further combines it with an emotion engine that recognizes the user's emotions. This system transmits the resume entered by the user to a server, which analyzes its contents and generates revision suggestions. The system includes a process in which the user revises the resume based on the suggestions, and the server then suggests optimal job information. Furthermore, the emotion engine recognizes the user's emotions and reflects them in the revision suggestions, providing more appropriate support.

[1642] System Overview

[1643] Enter your resume

[1644] User:

[1645] A user enters their resume into a text editor in the application. For example, user A enters the following:

[1646] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[1647] Sending data

[1648] Device:

[1649] The resume data entered by the user is sent to the server. The HTTPS protocol is used to ensure a secure connection. For example, the following JSON data is sent:

[1650] POST / api / submitResume HTTP / 1.1

[1651] Host: resume-advisor.example.com

[1652] Content-Type: application / json

[1653] {

[1654] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[1655] }

[1656] Data analysis

[1657] server:

[1658] The server analyzes the received resume text data. First, the server converts the received data from JSON format to text data for analysis.

[1659] Next, we use GPT-3, a generative AI model, to evaluate the grammar and structure of the resume. For example, we give GPT-3 the following input to analyze it:

[1660] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[1661] Generate correction suggestions

[1662] server:

[1663] The server generates revision suggestions for the user's resume based on the results of GPT-3 analysis. These revision suggestions include new wording suggestions, corrected phrases, and restructured sentences. For example, it generates the following revision suggestions:

[1664] Current position: Project Manager (5 years)

[1665] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1666] Emotion recognition by emotion engine

[1667] Emotion Engine:

[1668] The emotion engine analyzes emotions based on user input and operational context, for example, analyzing how users react to suggested edits (e.g., frustration, joy, confusion) in real time.

[1669] Adjusting proposed changes

[1670] server:

[1671] The server adjusts the tone and content of the correction suggestions based on the output of the emotion engine. For example, if the user is feeling stressed, it will take a softer approach to the suggestions.

[1672] Below is an example of an adjustment suggested by the emotion engine.

[1673] Current position: Project Manager (5 years)

[1674] Responsibilities: I was responsible for properly understanding the client's requirements, managing the project progress smoothly, and ensuring delivery deadlines were met.

[1675] Submit and review your proposal

[1676] server:

[1677] The generated correction suggestions are sent to the user's device in JSON format.

[1678] HTTP / 1.1 200 OK

[1679] Content-Type: application / json

[1680] {

[1681] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[1682] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[1683] }

[1684] User:

[1685] The user checks the suggestions from the server and corrects his / her resume. For example, he / she makes the following corrections according to the suggestions.

[1686] Current position: Project Manager (5 years)

[1687] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1688] Submit new data and reassess

[1689] Device:

[1690] The corrected resume data is sent to the server again.

[1691] POST / api / submitResume HTTP / 1.1

[1692] Host: resume-advisor.example.com

[1693] Content-Type: application / json

[1694] {

[1695] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[1696] }

[1697] server:

[1698] Re-analyze the received revised resume and evaluate whether there are any further improvements. If necessary, generate and send another revision proposal.

[1699] Providing job information

[1700] server:

[1701] The user enters data to register their career history, skills, and desired job type. For example, User A registers the following data.

[1702] {

[1703] "career": "5 years of experience as a project manager",

[1704] "skills": "Project management, customer relations, delivery management",

[1705] "desiredPosition": "Project Manager"

[1706] }

[1707] server:

[1708] The server analyzes the user's career history, skills, and desired job type, and proposes the most suitable job information. For example, it generates the following job information:

[1709] {

[1710] "jobSuggestions": [

[1711] {

[1712] "company": "IT company B",

[1713] "position": "Project Manager",

[1714] "location": "Tokyo",

[1715] "description": "Responsible for managing large projects and customer relations."

[1716] }

[1717] ]

[1718] }

[1719] Device:

[1720] The proposed job listings are displayed to the user, who can then select the job that interests them and proceed with the application process.

[1721] The processing flow will be explained below.

[1722] Step 1:

[1723] A user enters a resume into a text editor within the application. For example, the user enters the following text:

[1724] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[1725] Step 2:

[1726] The terminal sends the resume data entered by the user to the server. The HTTPS protocol is used to ensure a secure connection. For example, the following JSON data is sent:

[1727] POST / api / submitResume HTTP / 1.1

[1728] Host: resume-advisor.example.com

[1729] Content-Type: application / json

[1730] {

[1731] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[1732] }

[1733] Step 3:

[1734] The server analyzes the text data of the resume it receives. First, the server converts the received data from JSON format to text data for analysis.

[1735] Step 4:

[1736] The server uses the generative AI model GPT-3 to evaluate the grammar and structure of the resume. For example, it gives prompts like the following to GPT-3:

[1737] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[1738] Step 5:

[1739] The server generates revision suggestions for the user's resume based on the GPT-3 response. These revision suggestions include new wording suggestions, phrase corrections, and sentence restructuring. For example, the following revision suggestions are generated:

[1740] Current position: Project Manager (5 years)

[1741] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1742] Step 6:

[1743] The emotion engine analyzes emotions based on the user's input and operational status. For example, it analyzes in real time whether the user is feeling stressed about the suggested corrections.

[1744] Step 7:

[1745] The server adjusts the tone and content of the correction suggestions based on the output of the emotion engine. For example, if the user is feeling stressed, it will adopt a softer tone approach. Below is an example of an adjusted correction suggestion.

[1746] Current position: Project Manager (5 years)

[1747] Responsibilities: I was responsible for properly understanding the client's requirements, managing the project progress smoothly, and ensuring delivery deadlines were met.

[1748] Step 8:

[1749] The server generates correction suggestions and sends them to the user's device in JSON format.

[1750] HTTP / 1.1 200 OK

[1751] Content-Type: application / json

[1752] {

[1753] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[1754] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[1755] }

[1756] Step 9:

[1757] The user checks the suggestions from the server and corrects the resume. For example, the user corrects the resume as follows according to the suggestions.

[1758] Current position: Project Manager (5 years)

[1759] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1760] Step 10:

[1761] The terminal transmits the corrected resume data to the server again.

[1762] POST / api / submitResume HTTP / 1.1

[1763] Host: resume-advisor.example.com

[1764] Content-Type: application / json

[1765] {

[1766] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[1767] }

[1768] Step 11:

[1769] The server re-analyzes the received revised resume and evaluates whether there are any further improvements, and if necessary, generates and sends another revision proposal.

[1770] Step 12:

[1771] The user enters data to register their career history, skills, and desired job type. For example, User A registers the following data.

[1772] {

[1773] "career": "5 years of experience as a project manager",

[1774] "skills": "Project management, customer relations, delivery management",

[1775] "desiredPosition": "Project Manager"

[1776] }

[1777] Step 13:

[1778] The server analyzes the user's career history, skills, and desired job type, and proposes the most suitable job information. For example, it generates the following job information:

[1779] {

[1780] "jobSuggestions": [

[1781] {

[1782] "company": "IT company",

[1783] "position": "Project Manager",

[1784] "location": "Tokyo",

[1785] "description": "Responsible for managing large projects and customer relations."

[1786] }

[1787] ]

[1788] }

[1789] Step 14:

[1790] The device displays the suggested job listings to the user, who can then select the job that interests them and proceed with the application process.

[1791] Example 2

[1792] 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."

[1793] Conventional resume creation support systems lack the functionality to automatically correct and optimize the content entered by the user, and do not provide support that takes the user's emotions into consideration. This can cause users to feel stressed. Furthermore, the lack of a function to suggest optimal job opportunities poses a challenge, making job searches less efficient.

[1794] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1795] In this invention, the server includes: means for a user to input their resume; means for transmitting the resume to the server; means for the server to analyze the text of the resume; means for generating revision suggestions based on the analysis results using a generative AI model; means including an emotion recognition engine that recognizes the user's emotions; means for adjusting the revision suggestions based on the output of the emotion recognition engine; means for transmitting the revision suggestions to the user; and means for the user to revise their resume based on the revision suggestions. This makes it possible to efficiently revise and optimize the user's resume, provide support that takes the user's emotions into consideration, and further, by suggesting optimal employment opportunities, enable efficient job hunting.

[1796] "User" refers to an individual who enters a resume and receives suggested revisions.

[1797] "Terminal" refers to an electronic device that allows a user to input a resume and transmit and receive data to and from a server.

[1798] "Server" refers to the computer system that analyzes resumes, generates revision suggestions, recognizes emotions, and makes job suggestions.

[1799] A "resume" refers to a document that lists a user's work history, skills, responsibilities, etc.

[1800] "Generative AI model" refers to the artificial intelligence algorithm used to analyze the content of a resume and generate suggested revisions.

[1801] An "emotion recognition engine" refers to a system that analyzes a user's emotions in real time and uses them to adjust suggested corrections.

[1802] "Suggested revisions" refers to the revisions the generative AI model suggests for improvement after evaluating the grammar and structure of the resume.

[1803] "Job information" refers to information about job opportunities suggested based on the user's career history, skills, and desired job type.

[1804] "Analysis" refers to the process of breaking down the content of a resume and evaluating its grammar and structure.

[1805] "Secure Connection" means an encrypted network connection for secure data communication.

[1806] The present invention relates to a system for efficiently improving a resume and providing support that takes into account the user's feelings. Specifically, the system involves a series of processes: inputting a user's resume, analyzing it, generating revision suggestions, and suggesting optimal job information.

[1807] To implement this system, the following hardware and software are used.

[1808] Hardware and software used

[1809] 1. Terminal: An electronic device on which a user inputs their resume and sends and receives data to and from the server. Examples include a PC or smartphone.

[1810] 2. Server: A computer system that analyzes resumes, generates revision suggestions, recognizes emotions, and proposes job information. The server is equipped with a high-performance CPU and large-capacity memory, and is installed with a database management system and an AI model operation environment.

[1811] 3. Generative AI model: An artificial intelligence algorithm used to analyze resume content and generate revision suggestions. A specific example is GPT-3 (Generative Pre-trained Transformer 3).

[1812] 4. Emotion Recognition Engine: A system that analyzes user emotions in real time and uses them to adjust revision suggestions. Software that implements specific emotion recognition algorithms is required.

[1813] Example of a system

[1814] Enter your resume

[1815] User: Enter their resume details into the text editor within the application. For example, enter the following:

[1816] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[1817] Sending data

[1818] Terminal: The resume data entered by the user is sent to the server, using the HTTPS protocol to ensure a secure connection.

[1819] Data analysis

[1820] Server: To analyze the received resume text data, the server converts the received data from JSON format to text data for analysis. Next, it uses the generative AI model GPT-3 to evaluate the grammar and structure. For example, it provides the following prompt sentence to GPT-3:

[1821] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[1822] Generate correction suggestions

[1823] Server: Based on the results of GPT-3 analysis, the server generates suggested revisions to the resume. For example, this includes suggesting new wording, correcting phrases, and restructuring sentences. Specific examples of suggested revisions include:

[1824] Current position: Project Manager (5 years)

[1825] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1826] Emotion recognition using an emotion recognition engine

[1827] Emotion Recognition Engine: Analyzes the user's reactions to suggested revisions. The emotion recognition engine recognizes the user's emotions, such as frustration, joy, and confusion, in real time.

[1828] Adjusting proposed changes

[1829] Server: Based on the output of the emotion recognition engine, the tone and content of the correction suggestions are adjusted. For example, if the user is feeling stressed, the suggestion is softened by the following:

[1830] Current position: Project Manager (5 years)

[1831] Responsibilities: I was responsible for properly understanding the client's requirements, managing the project progress smoothly, and ensuring delivery deadlines were met.

[1832] Submit and review your proposal

[1833] Server: The generated revision suggestions are sent in JSON format to the user's device. The user checks the revision suggestions from the server and revise their resume based on them.

[1834] In this way, the system of the present invention allows users to efficiently improve their resumes and obtain optimal job information while receiving appropriate support using emotion recognition.

[1835] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1836] Step 1: Enter your resume

[1837] User: Enter your resume into the text editor within the application. For example, enter the following:

[1838] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[1839] Input: The action of a user typing their resume into a text editor.

[1840] Output: The resume text saved in a text editor.

[1841] Step 2: Sending data

[1842] Terminal: The text data of the entered resume is sent to the server using the HTTPS protocol to ensure a secure connection.

[1843] json

[1844] POST / api / submitResume HTTP / 1.1

[1845] Host: resume-advisor.example.com

[1846] Content-Type: application / json

[1847] {

[1848] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[1849] }

[1850] Input: Resume data in a text editor.

[1851] Output: Text data of the submitted resume.

[1852] Step 3: Analyze the data

[1853] Server: Converts the received resume text data from JSON format to text data for analysis. Next, it uses the generative AI model GPT-3 to evaluate grammar and structure.

[1854] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[1855] Input: JSON data of the submitted resume.

[1856] Output: Analysis results by GPT-3.

[1857] Step 4: Generate correction suggestions

[1858] Server: Generates correction suggestions based on the results of GPT-3 analysis, such as proposing new wording or restructuring sentences.

[1859] Current position: Project Manager (5 years)

[1860] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1861] Input: Analysis results by GPT-3.

[1862] Output: Text data of suggested corrections.

[1863] Step 5: Emotion recognition by the emotion recognition engine

[1864] Emotion recognition engine: Analyzes emotions based on user input and operation status. For example, it analyzes how users react to suggested corrections (e.g., irritation, joy, confusion) in real time.

[1865] Input: User response data.

[1866] Output: User sentiment analysis results.

[1867] Step 6: Adjust the proposed changes

[1868] Server: Based on the output of the emotion recognition engine, the tone and content of the correction suggestions are adjusted. For example, if the user is feeling stressed, the tone of the suggestions is softened.

[1869] Current position: Project Manager (5 years)

[1870] Responsibilities: I was responsible for properly understanding the client's requirements, managing the project progress smoothly, and ensuring delivery deadlines were met.

[1871] Input: User sentiment analysis results, initial correction suggestions.

[1872] Output: Text data with sentiment-sensitive revision suggestions.

[1873] Step 7: Submit and review your proposal

[1874] Server: The generated correction suggestions are sent to the user's device in JSON format.

[1875] json

[1876] HTTP / 1.1 200 OK

[1877] Content-Type: application / json

[1878] {

[1879] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[1880] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[1881] }

[1882] User: Check the suggested revisions from the server and revise the resume based on them.

[1883] Current position: Project Manager (5 years)

[1884] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[1885] Input: Emotion-sensitive revision suggestions.

[1886] Output: The corrected resume text data.

[1887] Step 8: Submit new data and reassess

[1888] Terminal: Send the corrected resume data to the server again.

[1889] json

[1890] POST / api / submitResume HTTP / 1.1

[1891] Host: resume-advisor.example.com

[1892] Content-Type: application / json

[1893] {

[1894] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[1895] }

[1896] Server: Re-analyzes the resubmitted revised resume and evaluates whether there are any further improvements needed. If necessary, generates revision suggestions again and sends them to the user.

[1897] Input: Text data of the revised resume.

[1898] Output: Text data of the final revision suggestions.

[1899] Step 9: Post a job offer

[1900] Server: Analyzes the data registered by users regarding their career history, skills, and desired job type, and proposes the most suitable job information. For example, it generates the following job information:

[1901] json

[1902] {

[1903] "jobSuggestions": [

[1904] {

[1905] "company": "IT company",

[1906] "position": "Project Manager",

[1907] "location": "Tokyo",

[1908] "description": "Responsible for managing large projects and customer relations."

[1909] }

[1910] ]

[1911] }

[1912] Input: User's background, skills, and desired job data.

[1913] Output: Data suggesting the best job listings.

[1914] Terminal: Displays suggested job information to the user, who can then select the job they are interested in and proceed with the application process.

[1915] (Application example 2)

[1916] 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."

[1917] In today's world, people are expected to be able to effectively express their thoughts and opinions and communicate better with others. However, opinions are often not conveyed properly due to individual expressiveness and emotional influences. In addition, when a user receives necessary suggestions or feedback, it is necessary to appropriately adjust the suggestions based on the detected user's emotions. Therefore, this invention aims to provide a system that supports more appropriate and effective communication by analyzing users' opinions and impressions in real time, improving the content, and utilizing an emotion engine to suggest modifications that match the user's emotions.

[1918] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to input their own information, means for transmitting the information to the server, means for the server to analyze the text of the information, means for generating a revision suggestion based on the analysis result, means for transmitting the revision suggestion to the user, means for the user to correct their information based on the revision suggestion, and means for recognizing the user's emotions using an emotion engine and adjusting the revision suggestion. This allows the user to effectively improve their own information while receiving suggestions that take their emotions into consideration, thereby improving the quality of self-expression and communication.

[1919] "User" refers to an individual who enters their information and uses the system.

[1920] "Information" refers to opinions, impressions, or other written content entered by the user.

[1921] A "server" is a computer system that receives and analyzes user-submitted information, and generates and transmits revision suggestions.

[1922] "Parsing" is the process of evaluating the grammar, structure, and content of user-entered information and generating appropriate correction suggestions.

[1923] "Suggested corrections" are suggestions for improving the information entered by the user, including new wording suggestions, corrected phrases, and restructured sentences.

[1924] An "emotion engine" is software or hardware that recognizes and analyzes a user's emotions.

[1925] "Adjusting" refers to appropriately changing the tone and content of the revision suggestion depending on the user's emotion as recognized by the emotion engine.

[1926] This invention is a system that allows users to input their own information (opinions, impressions, etc.) and efficiently improve it. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides more appropriate support.

[1927] System Overview

[1928] Enter and submit information

[1929] A user inputs their information into a text editor via a device such as a smartphone or smart glasses. For example, a user inputs their review of a movie as follows:

[1930] "This movie was moving, but I wish the climax had been a little more impressive."

[1931] The information entered by the user is sent to the server via a secure protocol (e.g., HTTPS).

[1932] Analysis of information

[1933] The server analyzes the received information. First, it converts the received data into text data, and then uses a generative AI model (e.g., GPT-3) to evaluate the grammar and structure of the information. For example, it analyzes the information by giving GPT-3 the following prompt sentence:

[1934] "Please make your comments more professional and concise: The film was moving, but I wish the climax was a little more impactful."

[1935] Generate correction suggestions

[1936] Based on the analysis results, the server will suggest how to correct the user's information. The suggested corrections include new wording, corrected phrases, and restructured sentences. For example, the server will generate the following correction suggestions:

[1937] "The film was very moving, but I thought there was room for an even stronger climax."

[1938] Emotion recognition and regulation with emotion engine

[1939] Emotion engines (e.g., EmoReact) analyze user emotions based on their input and operational context. For example, if a user is frustrated, the tone of the suggested corrections will be softened. Below is an example of an adjustment made by an emotion engine.

[1940] "The film was very moving, but I thought there was room for the climax to be even more impactful. I agree with you."

[1941] Submit and review your proposal

[1942] The server sends the generated revision suggestions to the user, who then confirms and corrects them.

[1943] Hardware and software used

[1944] Hardware: Smartphones, smart glasses, servers.

[1945] Software: GPT-3 (generative AI model), EmoReact (emotion engine), secure data transmission via HTTPS protocol.

[1946] A concrete example of a prompt from a generative AI model

[1947] 1. Prompts to improve your opinion:

[1948] "Please make your comments more professional and concise: The film was moving, but I wish the climax was a little more impactful."

[1949] 2. Emotion-awareness regulation reflection prompt:

[1950] "Please tone it down if the user is stressed: This movie was moving, but I wish the climax was a little more impactful. I agree with you."

[1951] In this way, users can effectively improve their information and receive appropriate emotional support.

[1952] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1953] Step 1:

[1954] A user inputs their information through a text editor on a smartphone or smart glasses. For example, a user may write their impression of a movie as, "This movie was moving, but I wish the climax had been more memorable."

[1955] input:

[1956] Text data of user opinions and impressions.

[1957] output:

[1958] The entered information is stored on the terminal and is ready to be sent to the next processing step.

[1959] Step 2:

[1960] The device securely transmits the entered information to the server using the HTTPS protocol, and the transmitted data is packaged in JSON format.

[1961] input:

[1962] Text data entered by the user.

[1963] output:

[1964] Text data sent to a server over a secure protocol.

[1965] Specific behavior:

[1966] The terminal converts the user's text data into JSON format and sends it to the server using the HTTPS protocol.

[1967] Step 3:

[1968] The server converts the received text data into text for analysis and feeds it to a generative AI model (e.g., GPT-3) to evaluate grammar and composition. For example, it uses a prompt sentence such as, "Please make the provided opinion more professional and concise: This movie was moving, but I think the climax could have been more impressive."

[1969] input:

[1970] Text data received in JSON format.

[1971] output:

[1972] Analysis results (correction suggestions) generated by the generative AI model.

[1973] Specific behavior:

[1974] The server extracts text from the JSON data and inputs it to GPT-3 along with a prompt sentence for analysis.

[1975] Step 4:

[1976] The server generates suggestions for correcting the user's information based on the analysis, including new wording, corrected phrases, and restructured sentences.

[1977] input:

[1978] Text data analyzed by a generative AI model.

[1979] output:

[1980] Text data of the proposed correction.

[1981] Specific behavior:

[1982] Based on the analysis results, the server generates text that suggests new phrases, corrections to phrases, and restructuring of sentences.

[1983] Step 5:

[1984] The server uses an emotion engine (e.g., EmoReact) to recognize the user's emotions in real time and adjust the tone and content of the correction suggestions accordingly, for example, to tone down the suggestion if the user is annoyed.

[1985] input:

[1986] Emotional data based on user input and operation status.

[1987] output:

[1988] Text data with sentiment-adjusted revision suggestions.

[1989] Specific behavior:

[1990] The server uses emotion recognition software to analyze the user's emotions and adjusts the tone and content of the revision suggestions based on the results.

[1991] Step 6:

[1992] The server then sends the generated correction suggestions to the user's device via a secure protocol, packaged in JSON format.

[1993] input:

[1994] Text data of the adjusted correction proposal.

[1995] output:

[1996] The suggested fixes sent to the user's device.

[1997] Specific behavior:

[1998] The server converts the proposed revisions into JSON format and sends them to the terminal using the HTTPS protocol.

[1999] Step 7:

[2000] The user checks the received correction suggestions and corrects his / her information. Based on the correction suggestions, the user updates the information.

[2001] input:

[2002] Text data of the suggested revision sent from the server.

[2003] output:

[2004] The text data of the corrected information.

[2005] Specific behavior:

[2006] The user reviews the received revision suggestions and updates the information by applying new wording, correcting phrases, and restructuring the sentence.

[2007] 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.

[2008] 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.

[2009] 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.

[2010] [Fourth embodiment]

[2011] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2012] 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.

[2013] 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).

[2014] 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.

[2015] 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.

[2016] 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).

[2017] 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.

[2018] 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.

[2019] 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.

[2020] 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.

[2021] 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.

[2022] 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.

[2023] 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."

[2024] The present invention is a system that allows job seekers to input their resumes and improve them efficiently. This system involves sending the resumes entered by users to a server, which analyzes the contents and generates suggestions for revision. The user then revises the resume based on the suggestions, and the server then suggests the most suitable job information.

[2025] System Overview

[2026] Enter your resume

[2027] User:

[2028] A user enters their resume into a text editor in the application. For example, user A enters the following:

[2029] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[2030] Sending data

[2031] Device:

[2032] The resume data entered by the user is sent to the server using the HTTPS protocol to ensure a secure connection.

[2033] POST / api / submitResume HTTP / 1.1

[2034] Host: resume-advisor.example.com

[2035] Content-Type: application / json

[2036] {

[2037] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[2038] }

[2039] Data analysis

[2040] server:

[2041] The server analyzes the text of the received resume and utilizes the generative AI model GPT-3 to evaluate grammar and structure.

[2042] For example, the following input is given to GPT-3 for analysis:

[2043] GPT-3: Rewrite the following resume section to be more professional and concise: I worked as a project manager for 5 years, listening to client requests, managing project progress and ensuring deadlines are met.

[2044] Generate correction suggestions

[2045] server:

[2046] The server generates revision suggestions for the user's resume based on the results of GPT-3 analysis. These revision suggestions include new wording suggestions, corrected phrases, and restructured sentences. For example, it generates the following revision suggestions:

[2047] Current position: Project Manager (5 years)

[2048] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[2049] Submit and review your proposal

[2050] server:

[2051] The generated revision suggestions are sent to the user's terminal.

[2052] HTTP / 1.1 200 OK

[2053] Content-Type: application / json

[2054] {

[2055] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[2056] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[2057] }

[2058] User:

[2059] The user checks the suggestions from the server and corrects his / her resume. For example, he / she makes the following corrections according to the suggestions.

[2060] Current position: Project Manager (5 years)

[2061] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[2062] Submit new data and reassess

[2063] Device:

[2064] The corrected resume data is sent to the server again.

[2065] POST / api / submitResume HTTP / 1.1

[2066] Host: resume-advisor.example.com

[2067] Content-Type: application / json

[2068] {

[2069] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[2070] }

[2071] server:

[2072] Re-analyze the received revised resume and evaluate whether there are any further improvements. If necessary, generate and send another revision proposal.

[2073] Providing job information

[2074] server:

[2075] The system analyzes the data registered by users about their career history, skills, and desired job type, and suggests the most suitable job information. For example, it generates the following job information:

[2076] json

[2077] {

[2078] "jobSuggestions": [

[2079] {

[2080] "company": "IT company B",

[2081] "position": "Project Manager",

[2082] "location": "Tokyo",

[2083] "description": "Responsible for managing large projects and customer relations."

[2084] }

[2085] ]

[2086] }

[2087] Device:

[2088] The proposed job listings are displayed to the user, who can then select the job that interests them and proceed with the application process.

[2089] The processing flow will be explained below.

[2090] Step 1:

[2091] A user enters a resume into a text editor within the application. For example, the user enters the following text:

[2092] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[2093] Step 2:

[2094] The terminal sends the resume data entered by the user to the server. The HTTPS protocol is used to ensure a secure connection. For example, the following JSON data is sent:

[2095] POST / api / submitResume HTTP / 1.1

[2096] Host: resume-advisor.example.com

[2097] Content-Type: application / json

[2098] {

[2099] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[2100] }

[2101] Step 3:

[2102] The server analyzes the text data of the resume it receives. First, the server converts the received data from JSON format to text data for analysis.

[2103] Step 4:

[2104] The server uses the generative AI model GPT-3 to evaluate the grammar and structure of the resume, providing prompts like the following to GPT-3:

[2105] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[2106] Step 5:

[2107] The server then uses the GPT-3 results to generate suggested revisions to the user's resume, including new wording suggestions, corrected phrases, and restructured sentences.

[2108] Current position: Project Manager (5 years)

[2109] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[2110] Step 6:

[2111] The server generates correction suggestions and sends them to the user's device in JSON format.

[2112] HTTP / 1.1 200 OK

[2113] Content-Type: application / json

[2114] {

[2115] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[2116] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[2117] }

[2118] Step 7:

[2119] The user checks the suggestions from the server and corrects his / her resume. The user makes the following corrections according to the suggestions.

[2120] Current position: Project Manager (5 years)

[2121] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[2122] Step 8:

[2123] The terminal transmits the corrected resume data to the server again.

[2124] POST / api / submitResume HTTP / 1.1

[2125] Host: resume-advisor.example.com

[2126] Content-Type: application / json

[2127] {

[2128] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[2129] }

[2130] Step 9:

[2131] The server re-analyzes the received revised resume and evaluates whether there are any further improvements, and if necessary, generates and sends another revision proposal.

[2132] Step 10:

[2133] The user enters data to register their career history, skills, and desired job type. For example, User A registers the following data.

[2134] {

[2135] "career": "5 years of experience as a project manager",

[2136] "skills": "Project management, customer relations, delivery management",

[2137] "desiredPosition": "Project Manager"

[2138] }

[2139] Step 11:

[2140] The server analyzes the user's career history, skills, and desired job type, and proposes the most suitable job information. For example, it generates the following job information:

[2141] {

[2142] "jobSuggestions": [

[2143] {

[2144] "company": "IT company B",

[2145] "position": "Project Manager",

[2146] "location": "Tokyo",

[2147] "description": "Responsible for managing large projects and customer relations."

[2148] }

[2149] ]

[2150] }

[2151] Step 12:

[2152] The device displays the suggested job listings to the user, who can then select the job that interests them and proceed with the application process.

[2153] Example 1

[2154] 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."

[2155] Conventional resume creation systems require users to manually edit resumes, which is time-consuming and labor-intensive. Finding appropriate job postings also requires users' own efforts. Furthermore, applying for a job without reviewing grammar and structure can reduce the effectiveness of job searches. Therefore, there is a need for a system that can efficiently improve resumes and provide optimal job postings.

[2156] 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.

[2157] In this invention, the server includes a means for a user to input their own resume, a means for transmitting the resume to the server using a data transmission device, a means for the server to analyze the resume text using a generative AI model, a means for generating revision suggestions based on the analysis results, a means for transmitting the revision suggestions to the user's terminal, and a means for the user to revise their resume based on the revision suggestions. This allows the user to quickly and efficiently improve their resume and receive optimal job information.

[2158] "User" refers to the individual or entity that creates, inputs, or modifies a resume.

[2159] "Resume" refers to a document that lists a user's work history, skills, achievements, qualifications, etc.

[2160] The "data transmission device" refers to hardware or software for transmitting the resume entered by the user to the server.

[2161] "Server" refers to a central processing unit that receives user-submitted resumes, analyzes them, and generates revision suggestions.

[2162] "Generative AI model" refers to an artificial intelligence platform that uses natural language processing technology to analyze resume text and generate revision suggestions.

[2163] "Analysis" refers to the process of using a generative AI model to evaluate the grammar, structure, and content of a resume to identify areas for improvement.

[2164] "Suggested revisions" refers to the resume improvement suggestions provided by the generative AI model based on the analysis results.

[2165] "Device" refers to the device (e.g., computer, tablet, smartphone, etc.) through which a user enters their resume and receives suggested revisions.

[2166] "Best-fit job information" refers to information about job opportunities selected based on the user's resume and registration information.

[2167] MODE FOR CARRYING OUT THE INVENTION

[2168] The present invention is a system for enabling job seekers to efficiently improve their resumes, which involves a series of processes in which a user inputs their resume, sends the data to a server, and the server analyzes it, generates suggestions for revision, and provides feedback to the user.

[2169] Hardware and software used

[2170] Hardware:

[2171] Devices: Computers, tablets, smartphones, etc.

[2172] Server: A central processing unit that performs high-performance data processing.

[2173] software:

[2174] Program: A custom application for sending, receiving, parsing resume data, and generating revision suggestions.

[2175] Generative AI model: An artificial intelligence platform that uses natural language processing techniques such as OpenAI's GPT-3.

[2176] Specific operation of the system

[2177] User:

[2178] The user enters their resume into a text editor within the application, for example by entering the following:

[2179] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[2180] Device:

[2181] The terminal sends the entered resume to the server using the HTTPS protocol, with end-to-end encryption used during the transmission process to ensure data security.

[2182] server:

[2183] The server analyzes the text of the received resume. For this analysis, it uses the generative AI model GPT-3. The server starts the analysis by sending the following prompt to GPT-3:

[2184] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[2185] server:

[2186] Based on the analysis results of GPT-3, correction suggestions are generated. These correction suggestions include new wording suggestions, phrase corrections, and sentence restructuring. An example of a generated correction suggestion is as follows:

[2187] Current position: Project Manager (5 years)

[2188] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[2189] server:

[2190] The generated revision suggestions are sent to the user's terminal, and feedback is provided for the user to re-revise their resume. The revised resume data is sent back to the server for re-evaluation.

[2191] server:

[2192] Finally, the app will suggest suitable job listings based on the user's resume and registered information, including details such as company name, position, location, and job description.

[2193] Specific examples

[2194] For example, if User A enters his / her resume and sends it with the following message, "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met," the server will analyze it using GPT-3, a generative AI model, and return the following suggested revisions to User A:

[2195] Current position: Project Manager (5 years)

[2196] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[2197] User A then follows the suggestions to revise their resume and undergo further reevaluation to refine it to the best possible form. Ultimately, User A is presented with job information that best suits their background and skills, enabling them to efficiently search for a job.

[2198] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2199] Step 1: User enters resume

[2200] Input: User's resume text

[2201] Output: Input resume data

[2202] Specific behavior: A user enters their resume into a text editor in the application. For example, the user enters the following text:

[2203] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[2204] Step 2: Submit your resume

[2205] Input: User-entered resume data

[2206] Output: Resume data sent to the server

[2207] Specific operation: The terminal sends the resume data entered by the user to the server using the HTTPS protocol. The JSON format for sending is as follows:

[2208] POST / api / submitResume HTTP / 1.1

[2209] Host: resume-advisor.example.com

[2210] Content-Type: application / json

[2211] {

[2212] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[2213] }

[2214] Step 3: Analyze resume data

[2215] Input: Resume data sent to the server

[2216] Output: Generates analysis results AI model input data

[2217] Specific operation: The server analyzes the text of the received resume. This analysis is performed using OpenAI's generative AI model, GPT-3. The server sends the following prompt to GPT-3:

[2218] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[2219] Step 4: Generate correction suggestions

[2220] Input: Analysis results from a generative AI model

[2221] Output: Proposed correction data

[2222] Specific operation: The server generates correction suggestions based on the analysis results of GPT-3. These correction suggestions include new wording suggestions, phrase corrections, and sentence restructuring. For example, the following correction suggestions are generated:

[2223] Current position: Project Manager (5 years)

[2224] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[2225] Step 5: Submit your proposed revision

[2226] Input: Proposed correction data

[2227] Output: Suggested correction data sent to the user's device

[2228] Specific operation: The server sends the generated revision suggestions to the user's device, after which the user can revise their resume based on the suggestions.

[2229] Step 6: User revises resume

[2230] Input: Suggested correction data sent to the user's device

[2231] Output: Corrected resume data

[2232] Specific operation: The user checks the suggestions from the server and modifies his / her resume. For example, he / she modifies his / her resume based on the suggestions as follows:

[2233] Current position: Project Manager (5 years)

[2234] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[2235] Step 7: Resubmit your revised resume

[2236] Input: Revised resume data

[2237] Output: Resent resume data

[2238] Specific operation: The device sends the corrected resume data to the server again, again using the HTTPS protocol.

[2239] Step 8: Reassess your resume

[2240] Input: Resent resume data

[2241] Output: Secondary correction suggestions or evaluation data showing that no improvement is necessary

[2242] Specific behavior: The server re-analyzes the revised resume and either generates revision suggestions again or evaluates it as not requiring revision.

[2243] Step 9: Provide the best job offers

[2244] Input: Revised resume data and user registration information

[2245] Output: Optimal job posting data

[2246] Specific operation: The server will suggest the most suitable job information based on the user's revised resume and registered information. For example, the following job information will be generated.

[2247] Company Name: Technology Company

[2248] Job title: Project Manager

[2249] Location: Tokyo

[2250] Description: Responsible for managing large scale projects and customer relations.

[2251] This allows users to efficiently improve their resumes and find the best job opportunities.

[2252] (Application example 1)

[2253] 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."

[2254] In recent years, job seekers have been required to accurately and effectively describe their career history, but there is a lack of easy ways to do so. In particular, there is a need for a method that allows busy users, especially those in the midst of a job search, to create high-quality resumes without spending a lot of time. Furthermore, in order to quickly obtain appropriate job information, an advanced system that can perform detailed analysis of the user's career history and preferences is required. A new system that can solve these issues and improve user convenience is needed.

[2255] 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.

[2256] In this invention, the server includes means for a user to input their own resume, means for transmitting the resume to the server, means for the server to analyze the text of the resume, means for generating revision suggestions based on the analysis results, means for transmitting the revision suggestions to the user, means for the user to revise their resume based on the revision suggestions, means for converting voice input into text, and means for displaying the analysis results on the smart glasses. This allows the user to create a resume by voice input and further revise it while receiving feedback through the smart glasses, allowing them to easily and quickly obtain optimal job information.

[2257] "User" refers to an individual who uses the system to input or modify their resume.

[2258] A "resume" is a document that lists a user's work history, skills, career history, etc.

[2259] "Server" refers to a computer system that receives and analyzes data sent by users, and generates and returns suggested modifications.

[2260] "Voice input" is a method in which a user inputs information using voice.

[2261] "Text conversion" is the process of converting voice-input data into text form.

[2262] "Analysis means" refers to the function by which the server analyzes the resume, evaluates its contents, and identifies areas for improvement.

[2263] "Suggested revisions" refers to suggestions for improvements to the resume or new wording that the server provides to the user based on the analysis results.

[2264] "Smart glasses" are wearable devices that can visually display revision suggestions and other information to the user.

[2265] The present invention provides a system for users to efficiently improve their resumes. This system includes a series of processes, including voice input, text conversion, analysis, suggested revisions, feedback using smart glasses, and suggestion of optimal job information. An embodiment of this system will be described in detail below.

[2266] Voice to text conversion

[2267] The user uses the smart glasses to input voice data. For example, the user might say, "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met." This voice data is converted into text using the Google Speech-to-Text API.

[2268] Submit your resume

[2269] The device then uses the HTTPS protocol to transmit the converted text data to a server that uses the SSL / TLS protocol to ensure a secure connection.

[2270] Data analysis

[2271] The server analyzes the received resume text data using a generative AI model (GPT-3). The following prompt sentence is used for the analysis:

[2272] "Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years. I listened to client requests, managed project progress, and ensured deadlines were met."

[2273] Generation of correction suggestions and feedback

[2274] The server generates correction suggestions based on the results of GPT-3 analysis. For example, these correction suggestions may look like this:

[2275] Current position: Project Manager (5 years) Responsibilities: Understand customer requirements, manage project progress and ensure delivery deadlines.

[2276] The generated revision suggestions are visually fed back to the user through the smart glasses, allowing the user to review them and revise their resume.

[2277] Providing job information

[2278] The server generates optimal job information based on the user's revised resume and registered data (career history, skills, desired job type). For example, it provides the following job information:

[2279] "Company: IT Company B Position: Project Manager Location: Tokyo Description: Responsible for managing large-scale projects and dealing with customers."

[2280] This job information is visually displayed to the user using the smart glasses, allowing the user to select jobs that interest them and proceed with the application process.

[2281] In this way, the present invention allows users to effortlessly improve their resumes and quickly obtain the most suitable job information.

[2282] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2283] Step 1:

[2284] The user inputs voice data through the smart glasses. For example, the user might say, "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured delivery deadlines were met." This input voice data is captured by a microphone built into the smart glasses.

[2285] Step 2:

[2286] The device (smart glasses) converts the input voice data into text. To do this, the device calls the Google Speech-to-Text API to convert the voice data into text format. The input is the captured voice data, and the output is the text data corresponding to the voice content.

[2287] Step 3:

[2288] The terminal sends text data to the server using the HTTPS protocol to ensure confidentiality and integrity of the data. The input is the text data converted from the voice, and the output is a response confirming the data sent to the server.

[2289] Step 4:

[2290] The server analyzes the received text data. A generative AI model (GPT-3) is used for this analysis. Specifically, the server provides the text data to GPT-3 using the following prompt: "Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met." The input is the received text data, and the output is the correction suggestions generated by the analysis.

[2291] Step 5:

[2292] The server sends the generated correction suggestions back to the device. This transmission is also done using the HTTPS protocol. The input is the analysis result by GPT-3, i.e., the correction suggestions, and the output is the correction suggestions data sent to the device.

[2293] Step 6:

[2294] The terminal displays the suggested revisions on the display of the smart glasses. The user checks this visual feedback and revises the resume content as necessary. The input is the suggested revision data received from the server, and the output is the suggested revisions displayed on the display of the smart glasses.

[2295] Step 7:

[2296] The user corrects the resume based on the suggested corrections and sends it back to the server. The input is the resume text corrected by the user, and the output is the corrected data sent to the server.

[2297] Step 8:

[2298] The server generates optimal job listings based on the user's revised resume and registered data (career history, skills, desired job type). This is done using GPT-3 again. The input is the user's revised resume and registered information, and the output is the generated job listing.

[2299] Step 9:

[2300] The server sends the generated job information to the terminal, and the terminal displays the job information on the display of the smart glasses. The input is the generated job information, and the output is the job information visually displayed on the display of the smart glasses.

[2301] In this way, the present invention allows users to effortlessly improve their resumes and quickly obtain the most suitable job information.

[2302] 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.

[2303] The present invention provides a system that allows job seekers to input their resumes and efficiently improve them, and further combines it with an emotion engine that recognizes the user's emotions. This system transmits the resume entered by the user to a server, which analyzes its contents and generates revision suggestions. The system includes a process in which the user revises the resume based on the suggestions, and the server then suggests optimal job information. Furthermore, the emotion engine recognizes the user's emotions and reflects them in the revision suggestions, providing more appropriate support.

[2304] System Overview

[2305] Enter your resume

[2306] User:

[2307] A user enters their resume into a text editor in the application. For example, user A enters the following:

[2308] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[2309] Sending data

[2310] Device:

[2311] The resume data entered by the user is sent to the server. The HTTPS protocol is used to ensure a secure connection. For example, the following JSON data is sent:

[2312] POST / api / submitResume HTTP / 1.1

[2313] Host: resume-advisor.example.com

[2314] Content-Type: application / json

[2315] {

[2316] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[2317] }

[2318] Data analysis

[2319] server:

[2320] The server analyzes the received resume text data. First, the server converts the received data from JSON format to text data for analysis.

[2321] Next, we use GPT-3, a generative AI model, to evaluate the grammar and structure of the resume. For example, we give GPT-3 the following input to analyze it:

[2322] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[2323] Generate correction suggestions

[2324] server:

[2325] The server generates revision suggestions for the user's resume based on the results of GPT-3 analysis. These revision suggestions include new wording suggestions, corrected phrases, and restructured sentences. For example, it generates the following revision suggestions:

[2326] Current position: Project Manager (5 years)

[2327] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[2328] Emotion recognition by emotion engine

[2329] Emotion Engine:

[2330] The emotion engine analyzes emotions based on user input and operational context, for example, analyzing how users react to suggested edits (e.g., frustration, joy, confusion) in real time.

[2331] Adjusting proposed changes

[2332] server:

[2333] The server adjusts the tone and content of the correction suggestions based on the output of the emotion engine. For example, if the user is feeling stressed, it will take a softer approach to the suggestions.

[2334] Below is an example of an adjustment suggested by the emotion engine.

[2335] Current position: Project Manager (5 years)

[2336] Responsibilities: I was responsible for properly understanding the client's requirements, managing the project progress smoothly, and ensuring delivery deadlines were met.

[2337] Submit and review your proposal

[2338] server:

[2339] The generated correction suggestions are sent to the user's device in JSON format.

[2340] HTTP / 1.1 200 OK

[2341] Content-Type: application / json

[2342] {

[2343] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[2344] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[2345] }

[2346] User:

[2347] The user checks the suggestions from the server and corrects his / her resume. For example, he / she makes the following corrections according to the suggestions.

[2348] Current position: Project Manager (5 years)

[2349] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[2350] Submit new data and reassess

[2351] Device:

[2352] The corrected resume data is sent to the server again.

[2353] POST / api / submitResume HTTP / 1.1

[2354] Host: resume-advisor.example.com

[2355] Content-Type: application / json

[2356] {

[2357] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[2358] }

[2359] server:

[2360] Re-analyze the received revised resume and evaluate whether there are any further improvements. If necessary, generate and send another revision proposal.

[2361] Providing job information

[2362] server:

[2363] The user enters data to register their career history, skills, and desired job type. For example, User A registers the following data.

[2364] {

[2365] "career": "5 years of experience as a project manager",

[2366] "skills": "Project management, customer relations, delivery management",

[2367] "desiredPosition": "Project Manager"

[2368] }

[2369] server:

[2370] The server analyzes the user's career history, skills, and desired job type, and proposes the most suitable job information. For example, it generates the following job information:

[2371] {

[2372] "jobSuggestions": [

[2373] {

[2374] "company": "IT company B",

[2375] "position": "Project Manager",

[2376] "location": "Tokyo",

[2377] "description": "Responsible for managing large projects and customer relations."

[2378] }

[2379] ]

[2380] }

[2381] Device:

[2382] The proposed job listings are displayed to the user, who can then select the job that interests them and proceed with the application process.

[2383] The processing flow will be explained below.

[2384] Step 1:

[2385] A user enters a resume into a text editor within the application. For example, the user enters the following text:

[2386] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[2387] Step 2:

[2388] The terminal sends the resume data entered by the user to the server. The HTTPS protocol is used to ensure a secure connection. For example, the following JSON data is sent:

[2389] POST / api / submitResume HTTP / 1.1

[2390] Host: resume-advisor.example.com

[2391] Content-Type: application / json

[2392] {

[2393] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[2394] }

[2395] Step 3:

[2396] The server analyzes the text data of the resume it receives. First, the server converts the received data from JSON format to text data for analysis.

[2397] Step 4:

[2398] The server uses the generative AI model GPT-3 to evaluate the grammar and structure of the resume. For example, it gives prompts like the following to GPT-3:

[2399] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[2400] Step 5:

[2401] The server generates revision suggestions for the user's resume based on the GPT-3 response. These revision suggestions include new wording suggestions, phrase corrections, and sentence restructuring. For example, the following revision suggestions are generated:

[2402] Current position: Project Manager (5 years)

[2403] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[2404] Step 6:

[2405] The emotion engine analyzes emotions based on the user's input and operational status. For example, it analyzes in real time whether the user is feeling stressed about the suggested corrections.

[2406] Step 7:

[2407] The server adjusts the tone and content of the correction suggestions based on the output of the emotion engine. For example, if the user is feeling stressed, it will adopt a softer tone approach. Below is an example of an adjusted correction suggestion.

[2408] Current position: Project Manager (5 years)

[2409] Responsibilities: I was responsible for properly understanding the client's requirements, managing the project progress smoothly, and ensuring delivery deadlines were met.

[2410] Step 8:

[2411] The server generates correction suggestions and sends them to the user's device in JSON format.

[2412] HTTP / 1.1 200 OK

[2413] Content-Type: application / json

[2414] {

[2415] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[2416] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[2417] }

[2418] Step 9:

[2419] The user checks the suggestions from the server and corrects the resume. For example, the user corrects the resume as follows according to the suggestions.

[2420] Current position: Project Manager (5 years)

[2421] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[2422] Step 10:

[2423] The terminal transmits the corrected resume data to the server again.

[2424] POST / api / submitResume HTTP / 1.1

[2425] Host: resume-advisor.example.com

[2426] Content-Type: application / json

[2427] {

[2428] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[2429] }

[2430] Step 11:

[2431] The server re-analyzes the received revised resume and evaluates whether there are any further improvements, and if necessary, generates and sends another revision proposal.

[2432] Step 12:

[2433] The user enters data to register their career history, skills, and desired job type. For example, User A registers the following data.

[2434] {

[2435] "career": "5 years of experience as a project manager",

[2436] "skills": "Project management, customer relations, delivery management",

[2437] "desiredPosition": "Project Manager"

[2438] }

[2439] Step 13:

[2440] The server analyzes the user's career history, skills, and desired job type, and proposes the most suitable job information. For example, it generates the following job information:

[2441] {

[2442] "jobSuggestions": [

[2443] {

[2444] "company": "IT company",

[2445] "position": "Project Manager",

[2446] "location": "Tokyo",

[2447] "description": "Responsible for managing large projects and customer relations."

[2448] }

[2449] ]

[2450] }

[2451] Step 14:

[2452] The device displays the suggested job listings to the user, who can then select the job that interests them and proceed with the application process.

[2453] Example 2

[2454] 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."

[2455] Conventional resume creation support systems lack the functionality to automatically correct and optimize the content entered by the user, and do not provide support that takes the user's emotions into consideration. This can cause users to feel stressed. Furthermore, the lack of a function to suggest optimal job opportunities poses a challenge, making job searches less efficient.

[2456] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2457] In this invention, the server includes: means for a user to input their resume; means for transmitting the resume to the server; means for the server to analyze the text of the resume; means for generating revision suggestions based on the analysis results using a generative AI model; means including an emotion recognition engine that recognizes the user's emotions; means for adjusting the revision suggestions based on the output of the emotion recognition engine; means for transmitting the revision suggestions to the user; and means for the user to revise their resume based on the revision suggestions. This makes it possible to efficiently revise and optimize the user's resume, provide support that takes the user's emotions into consideration, and further, by suggesting optimal employment opportunities, enable efficient job hunting.

[2458] "User" refers to an individual who enters a resume and receives suggested revisions.

[2459] "Terminal" refers to an electronic device that allows a user to input a resume and transmit and receive data to and from a server.

[2460] "Server" refers to the computer system that analyzes resumes, generates revision suggestions, recognizes emotions, and makes job suggestions.

[2461] A "resume" refers to a document that lists a user's work history, skills, responsibilities, etc.

[2462] "Generative AI model" refers to the artificial intelligence algorithm used to analyze the content of a resume and generate suggested revisions.

[2463] An "emotion recognition engine" refers to a system that analyzes a user's emotions in real time and uses them to adjust suggested corrections.

[2464] "Suggested revisions" refers to the revisions the generative AI model suggests for improvement after evaluating the grammar and structure of the resume.

[2465] "Job information" refers to information about job opportunities suggested based on the user's career history, skills, and desired job type.

[2466] "Analysis" refers to the process of breaking down the content of a resume and evaluating its grammar and structure.

[2467] "Secure Connection" means an encrypted network connection for secure data communication.

[2468] The present invention relates to a system for efficiently improving a resume and providing support that takes into account the user's feelings. Specifically, the system involves a series of processes: inputting a user's resume, analyzing it, generating revision suggestions, and suggesting optimal job information.

[2469] To implement this system, the following hardware and software are used.

[2470] Hardware and software used

[2471] 1. Terminal: An electronic device on which a user inputs their resume and sends and receives data to and from the server. Examples include a PC or smartphone.

[2472] 2. Server: A computer system that analyzes resumes, generates revision suggestions, recognizes emotions, and proposes job information. The server is equipped with a high-performance CPU and large-capacity memory, and is installed with a database management system and an AI model operation environment.

[2473] 3. Generative AI model: An artificial intelligence algorithm used to analyze resume content and generate revision suggestions. A specific example is GPT-3 (Generative Pre-trained Transformer 3).

[2474] 4. Emotion Recognition Engine: A system that analyzes user emotions in real time and uses them to adjust revision suggestions. Software that implements specific emotion recognition algorithms is required.

[2475] Example of a system

[2476] Enter your resume

[2477] User: Enter their resume details into the text editor within the application. For example, enter the following:

[2478] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[2479] Sending data

[2480] Terminal: The resume data entered by the user is sent to the server, using the HTTPS protocol to ensure a secure connection.

[2481] Data analysis

[2482] Server: To analyze the received resume text data, the server converts the received data from JSON format to text data for analysis. Next, it uses the generative AI model GPT-3 to evaluate the grammar and structure. For example, it provides the following prompt sentence to GPT-3:

[2483] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[2484] Generate correction suggestions

[2485] Server: Based on the results of GPT-3 analysis, the server generates suggested revisions to the resume. For example, this includes suggesting new wording, correcting phrases, and restructuring sentences. Specific examples of suggested revisions include:

[2486] Current position: Project Manager (5 years)

[2487] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[2488] Emotion recognition using an emotion recognition engine

[2489] Emotion Recognition Engine: Analyzes the user's reactions to suggested revisions. The emotion recognition engine recognizes the user's emotions, such as frustration, joy, and confusion, in real time.

[2490] Adjusting proposed changes

[2491] Server: Based on the output of the emotion recognition engine, the tone and content of the correction suggestions are adjusted. For example, if the user is feeling stressed, the suggestion is softened by the following:

[2492] Current position: Project Manager (5 years)

[2493] Responsibilities: I was responsible for properly understanding the client's requirements, managing the project progress smoothly, and ensuring delivery deadlines were met.

[2494] Submit and review your proposal

[2495] Server: The generated revision suggestions are sent in JSON format to the user's device. The user checks the revision suggestions from the server and revise their resume based on them.

[2496] In this way, the system of the present invention allows users to efficiently improve their resumes and obtain optimal job information while receiving appropriate support using emotion recognition.

[2497] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2498] Step 1: Enter your resume

[2499] User: Enter your resume into the text editor within the application. For example, enter the following:

[2500] I worked as a project manager for five years, listening to client requests, managing project progress and ensuring deadlines are met.

[2501] Input: The action of a user typing their resume into a text editor.

[2502] Output: The resume text saved in a text editor.

[2503] Step 2: Sending data

[2504] Terminal: The text data of the entered resume is sent to the server using the HTTPS protocol to ensure a secure connection.

[2505] json

[2506] POST / api / submitResume HTTP / 1.1

[2507] Host: resume-advisor.example.com

[2508] Content-Type: application / json

[2509] {

[2510] "resumeText": "I worked as a project manager for five years. I listened to customer requests, managed project progress, and ensured deadlines were met."

[2511] }

[2512] Input: Resume data in a text editor.

[2513] Output: Text data of the submitted resume.

[2514] Step 3: Analyze the data

[2515] Server: Converts the received resume text data from JSON format to text data for analysis. Next, it uses the generative AI model GPT-3 to evaluate grammar and structure.

[2516] Rewrite the following resume section to be more professional and concise: I worked as a project manager for five years, listening to client requests, managing project progress, and ensuring deadlines are met.

[2517] Input: JSON data of the submitted resume.

[2518] Output: Analysis results by GPT-3.

[2519] Step 4: Generate correction suggestions

[2520] Server: Generates correction suggestions based on the results of GPT-3 analysis, such as proposing new wording or restructuring sentences.

[2521] Current position: Project Manager (5 years)

[2522] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[2523] Input: Analysis results by GPT-3.

[2524] Output: Text data of suggested corrections.

[2525] Step 5: Emotion recognition by the emotion recognition engine

[2526] Emotion recognition engine: Analyzes emotions based on user input and operation status. For example, it analyzes how users react to suggested corrections (e.g., irritation, joy, confusion) in real time.

[2527] Input: User response data.

[2528] Output: User sentiment analysis results.

[2529] Step 6: Adjust the proposed changes

[2530] Server: Based on the output of the emotion recognition engine, the tone and content of the correction suggestions are adjusted. For example, if the user is feeling stressed, the tone of the suggestions is softened.

[2531] Current position: Project Manager (5 years)

[2532] Responsibilities: I was responsible for properly understanding the client's requirements, managing the project progress smoothly, and ensuring delivery deadlines were met.

[2533] Input: User sentiment analysis results, initial correction suggestions.

[2534] Output: Text data with sentiment-sensitive revision suggestions.

[2535] Step 7: Submit and review your proposal

[2536] Server: The generated correction suggestions are sent to the user's device in JSON format.

[2537] json

[2538] HTTP / 1.1 200 OK

[2539] Content-Type: application / json

[2540] {

[2541] "originalText": "I worked as a project manager for five years. I listened to customer requests, managed the progress of projects, and ensured deadlines were met.",

[2542] "suggestion": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery deadlines."

[2543] }

[2544] User: Check the suggested revisions from the server and revise the resume based on them.

[2545] Current position: Project Manager (5 years)

[2546] Responsibilities: Understand customer requirements, manage project progress and adhere to deadlines.

[2547] Input: Emotion-sensitive revision suggestions.

[2548] Output: The corrected resume text data.

[2549] Step 8: Submit new data and reassess

[2550] Terminal: Send the corrected resume data to the server again.

[2551] json

[2552] POST / api / submitResume HTTP / 1.1

[2553] Host: resume-advisor.example.com

[2554] Content-Type: application / json

[2555] {

[2556] "resumeText": "Current position: Project Manager (5 years)\nResponsibilities: Understand customer requirements, manage project progress, and ensure delivery on time."

[2557] }

[2558] Server: Re-analyzes the resubmitted revised resume and evaluates whether there are any further improvements needed. If necessary, generates revision suggestions again and sends them to the user.

[2559] Input: Text data of the revised resume.

[2560] Output: Text data of the final revision suggestions.

[2561] Step 9: Post a job offer

[2562] Server: Analyzes the data registered by users regarding their career history, skills, and desired job type, and proposes the most suitable job information. For example, it generates the following job information:

[2563] json

[2564] {

[2565] "jobSuggestions": [

[2566] {

[2567] "company": "IT company",

[2568] "position": "Project Manager",

[2569] "location": "Tokyo",

[2570] "description": "Responsible for managing large projects and customer relations."

[2571] }

[2572] ]

[2573] }

[2574] Input: User's background, skills, and desired job data.

[2575] Output: Data suggesting the best job listings.

[2576] Terminal: Displays suggested job information to the user, who can then select the job they are interested in and proceed with the application process.

[2577] (Application example 2)

[2578] 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."

[2579] In today's world, people are expected to be able to effectively express their thoughts and opinions and communicate better with others. However, opinions are often not conveyed properly due to individual expressiveness and emotional influences. In addition, when a user receives necessary suggestions or feedback, it is necessary to appropriately adjust the suggestions based on the detected user's emotions. Therefore, this invention aims to provide a system that supports more appropriate and effective communication by analyzing users' opinions and impressions in real time, improving the content, and utilizing an emotion engine to suggest modifications that match the user's emotions.

[2580] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to input their own information, means for transmitting the information to the server, means for the server to analyze the text of the information, means for generating a revision suggestion based on the analysis result, means for transmitting the revision suggestion to the user, means for the user to correct their information based on the revision suggestion, and means for recognizing the user's emotions using an emotion engine and adjusting the revision suggestion. This allows the user to effectively improve their own information while receiving suggestions that take their emotions into consideration, thereby improving the quality of self-expression and communication.

[2581] "User" refers to an individual who enters their information and uses the system.

[2582] "Information" refers to opinions, impressions, or other written content entered by the user.

[2583] A "server" is a computer system that receives and analyzes user-submitted information, and generates and transmits revision suggestions.

[2584] "Parsing" is the process of evaluating the grammar, structure, and content of user-entered information and generating appropriate correction suggestions.

[2585] "Suggested corrections" are suggestions for improving the information entered by the user, including new wording suggestions, corrected phrases, and restructured sentences.

[2586] An "emotion engine" is software or hardware that recognizes and analyzes a user's emotions.

[2587] "Adjusting" refers to appropriately changing the tone and content of the revision suggestion depending on the user's emotion as recognized by the emotion engine.

[2588] This invention is a system that allows users to input their own information (opinions, impressions, etc.) and efficiently improve it. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides more appropriate support.

[2589] System Overview

[2590] Enter and submit information

[2591] A user inputs their information into a text editor via a device such as a smartphone or smart glasses. For example, a user inputs their review of a movie as follows:

[2592] "This movie was moving, but I wish the climax had been a little more impressive."

[2593] The information entered by the user is sent to the server via a secure protocol (e.g., HTTPS).

[2594] Analysis of information

[2595] The server analyzes the received information. First, it converts the received data into text data, and then uses a generative AI model (e.g., GPT-3) to evaluate the grammar and structure of the information. For example, it analyzes the information by giving GPT-3 the following prompt sentence:

[2596] "Please make your comments more professional and concise: The film was moving, but I wish the climax was a little more impactful."

[2597] Generate correction suggestions

[2598] Based on the analysis results, the server will suggest how to correct the user's information. The suggested corrections include new wording, corrected phrases, and restructured sentences. For example, the server will generate the following correction suggestions:

[2599] "The film was very moving, but I thought there was room for an even stronger climax."

[2600] Emotion recognition and regulation with emotion engine

[2601] Emotion engines (e.g., EmoReact) analyze user emotions based on their input and operational context. For example, if a user is frustrated, the tone of the suggested corrections will be softened. Below is an example of an adjustment made by an emotion engine.

[2602] "The film was very moving, but I thought there was room for the climax to be even more impactful. I agree with you."

[2603] Submit and review your proposal

[2604] The server sends the generated revision suggestions to the user, who then confirms and corrects them.

[2605] Hardware and software used

[2606] Hardware: Smartphones, smart glasses, servers.

[2607] Software: GPT-3 (generative AI model), EmoReact (emotion engine), secure data transmission via HTTPS protocol.

[2608] A concrete example of a prompt from a generative AI model

[2609] 1. Prompts to improve your opinion:

[2610] "Please make your comments more professional and concise: The film was moving, but I wish the climax was a little more impactful."

[2611] 2. Emotion-awareness regulation reflection prompt:

[2612] "Please tone it down if the user is stressed: This movie was moving, but I wish the climax was a little more impactful. I agree with you."

[2613] In this way, users can effectively improve their information and receive appropriate emotional support.

[2614] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2615] Step 1:

[2616] A user inputs their information through a text editor on a smartphone or smart glasses. For example, a user may write their impression of a movie as, "This movie was moving, but I wish the climax had been more memorable."

[2617] input:

[2618] Text data of user opinions and impressions.

[2619] output:

[2620] The entered information is stored on the terminal and is ready to be sent to the next processing step.

[2621] Step 2:

[2622] The device securely transmits the entered information to the server using the HTTPS protocol, and the transmitted data is packaged in JSON format.

[2623] input:

[2624] Text data entered by the user.

[2625] output:

[2626] Text data sent to a server over a secure protocol.

[2627] Specific behavior:

[2628] The terminal converts the user's text data into JSON format and sends it to the server using the HTTPS protocol.

[2629] Step 3:

[2630] The server converts the received text data into text for analysis and feeds it to a generative AI model (e.g., GPT-3) to evaluate grammar and composition. For example, it uses a prompt sentence such as, "Please make the provided opinion more professional and concise: This movie was moving, but I think the climax could have been more impressive."

[2631] input:

[2632] Text data received in JSON format.

[2633] output:

[2634] Analysis results (correction suggestions) generated by the generative AI model.

[2635] Specific behavior:

[2636] The server extracts text from the JSON data and inputs it to GPT-3 along with a prompt sentence for analysis.

[2637] Step 4:

[2638] The server generates suggestions for correcting the user's information based on the analysis, including new wording, corrected phrases, and restructured sentences.

[2639] input:

[2640] Text data analyzed by a generative AI model.

[2641] output:

[2642] Text data of the proposed correction.

[2643] Specific behavior:

[2644] Based on the analysis results, the server generates text that suggests new phrases, corrections to phrases, and restructuring of sentences.

[2645] Step 5:

[2646] The server uses an emotion engine (e.g., EmoReact) to recognize the user's emotions in real time and adjust the tone and content of the correction suggestions accordingly, for example, to tone down the suggestion if the user is annoyed.

[2647] input:

[2648] Emotional data based on user input and operation status.

[2649] output:

[2650] Text data with sentiment-adjusted revision suggestions.

[2651] Specific behavior:

[2652] The server uses emotion recognition software to analyze the user's emotions and adjusts the tone and content of the revision suggestions based on the results.

[2653] Step 6:

[2654] The server then sends the generated correction suggestions to the user's device via a secure protocol, packaged in JSON format.

[2655] input:

[2656] Text data of the adjusted correction proposal.

[2657] output:

[2658] The suggested fixes sent to the user's device.

[2659] Specific behavior:

[2660] The server converts the proposed revisions into JSON format and sends them to the terminal using the HTTPS protocol.

[2661] Step 7:

[2662] The user checks the received correction suggestions and corrects his / her information. Based on the correction suggestions, the user updates the information.

[2663] input:

[2664] Text data of the suggested revision sent from the server.

[2665] output:

[2666] The text data of the corrected information.

[2667] Specific behavior:

[2668] The user reviews the received revision suggestions and updates the information by applying new wording, correcting phrases, and restructuring the sentence.

[2669] 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.

[2670] 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.

[2671] 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.

[2672] 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.

[2673] 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.

[2674] 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.

[2675] 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).

[2676] 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.

[2677] 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."

[2678] 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.

[2679] 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).

[2680] 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.

[2681] 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.

[2682] 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.

[2683] 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.

[2684] 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,...

Claims

1. a means for a user to input their resume; means for transmitting the resume to a server; A server analyzes the text of the resume; means for generating revision suggestions based on the analysis results; means for transmitting said revision suggestions to a user; A means for the user to amend the resume based on the proposed amendments; A system including:

2. 2. The system according to claim 1, wherein the server further comprises means for analyzing the user's career history, skills, and desired job type, and proposing the most suitable employment opportunity.

3. The system of claim 1 , wherein the suggested revisions include new wording suggestions, phrase corrections, and sentence restructurings.

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