Application form creation system, application form creation method, and program

Abstract

To actively propose an appropriate question to an applicant and consequently create an application form having higher possibility of being accepted.SOLUTION: An application form creation system which creates an application form acquires application point data indicating an application point with a document, generates hearing data from the application point data; acquires answer data to the hearing data; and generates an application document of the application form on the basis of the answer data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a technique that is effective in supporting the preparation of applications for subsidies, grants, grants, etc. provided by the private sector, government, etc. [Background technology]

[0002] In recent years, applications for grants, subsidies, subsidies, etc. have been submitted electronically. Applicants fill out application forms in accordance with application guidelines published on websites by government agencies and submit their applications. Such application systems to the government are also undergoing DX (Digital Transformation). For example, Patent Document 1 discloses an application procedure support system that streamlines the application process for grants and subsidies, and discloses that if there is any missing information required for the application, the applicant will be notified. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 7038273 Summary of the Invention [Problem to be solved by the invention]

[0004] However, in Patent Document 1, the applicant must proactively input the application items, and a person must actively create the application form. In addition, it is desirable to not only fill in all the fields on the application form without missing anything, but also to be able to prepare an application form that appropriately includes detailed company information, such as strengths, weaknesses, market evaluation, etc., based on interviews with companies, so that the application will ultimately be accepted.

[0005] In view of these problems, the present invention aims to provide an application preparation system, an application preparation method, and a program that actively propose appropriate questions to applicants and thereby prepare application forms that are more likely to be accepted. [Means for solving the problem]

[0006] The present invention provides an application creation system for creating an application form, an application guidelines data acquisition unit that acquires application guidelines data that show application guidelines in writing; a hearing data generation unit that generates hearing data from the application outline data; a response data acquisition unit that acquires response data to the hearing data; a document generation unit that generates an application document based on the response data; An application creation system is provided.

[0007] According to the present invention, by generating an application document based on response data to interview data based on application guidelines data, it is possible to actively suggest appropriate questions to the applicant, thereby creating an application document that is more likely to be accepted. [Effects of the Invention]

[0008] According to the present invention, it is possible to actively suggest appropriate questions to applicants, thereby enabling them to create application forms that are more likely to be accepted. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a schematic diagram for explaining an overview of an application form preparation system 1. [Figure 2] 1 is a block diagram showing the configuration of an application form preparation system 1. FIG. [Figure 3] FIG. 10 is a flowchart showing the hearing data generation process executed by the application form preparation system 1. [Figure 4]FIG. 10 is a flowchart showing a response data acquisition process executed by the application form preparation system 1. [Figure 5] FIG. 2 is a diagram schematically illustrating an example of a screen of applicant terminal 2. [Figure 6] FIG. 2 is a diagram schematically illustrating an example of a screen of applicant terminal 2. [Figure 7] FIG. 2 is a diagram schematically illustrating an example of a screen of applicant terminal 2. [Figure 8] FIG. 2 is a diagram schematically illustrating an example of a screen of applicant terminal 2. [Figure 9] FIG. 2 is a diagram schematically illustrating an example of a screen of applicant terminal 2. [Figure 10] FIG. 2 is a diagram schematically illustrating an example of a screen of applicant terminal 2. [Figure 11] FIG. 2 is a diagram schematically illustrating an example of a screen of applicant terminal 2. [Figure 12] FIG. 2 is a diagram schematically illustrating an example of a screen of applicant terminal 2. [Figure 13] FIG. 2 is a flowchart showing the application document generation process executed by the application form preparation system 1. [Figure 14] FIG. 10 is a flowchart showing a learning process executed by the application form preparation system 1. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, embodiments of the present invention (hereinafter referred to as "embodiments") will be described in detail with reference to the accompanying drawings. In the following drawings, the same elements are designated by the same numbers or symbols throughout the description of the embodiments.

[0011] [Application Form Creation System 1 Overview] 1 is a schematic diagram for explaining an overview of application form preparation system 1. Components of application form preparation system 1 will be described based on FIG. The application form preparation system 1 is a system for preparing application forms that comprises at least a computer 10 with server functionality. In this embodiment, in addition to the computer 10, the application form preparation system 1 also comprises an applicant terminal 2 used by the applicant, and an application guidelines database (hereinafter, the database may also be simply referred to as DB) 3 in which application guidelines data is registered. The applicant terminal 2 and application guidelines DB3 are connected to the computer 10 so as to be able to communicate data with each other, and the applicant terminal 2 is further connected to the application guidelines DB3 so as to be able to communicate data with each other. The applicant terminal 2 is a terminal device used by the applicant, and is a terminal device that displays the output content output by the computer 10, accepts input from the applicant, and transmits the accepted input content to the computer 10, etc. The application guidelines DB 3 is a DB in which application guidelines data is registered by a computer or the like having a predetermined server function. The computer 10 has a server function and may be realized, for example, by a single computer, or may be realized by multiple computers, such as a cloud computer. In this specification, a cloud computer may refer to either a computer that uses any computer in a scalable manner to perform a specific function, or a computer that includes multiple functional modules to realize a system and uses the functions in any combination.

[0012] An outline of the processing steps performed by the application form preparation system 1 when preparing an application form will be described.

[0013] The computer 10 acquires application guidelines data that shows application guidelines in writing (step S1). The computer 10 obtains application guidelines data from the applicant terminal 2, which is a written document of the application guidelines (eligible applicants, application period, application conditions, etc.) when applying for subsidies, grants, grants, etc. that the applicant terminal 2 has obtained from the application guidelines DB3. The computer 10 may also be configured to acquire application guidelines data from the application guidelines DB 3 rather than from the applicant terminal 2.

[0014] The computer 10 generates interview data from the application guidelines data (step S2). The computer 10 generates hearing data (questions necessary for generating an application form, options for those questions, etc.) from the acquired application guidelines data using a large-scale language model. The computer 10 inputs this application guidelines data into the large-scale language model, obtains hearing data as an output result, and generates hearing data from the application guidelines data. The computer 10 outputs the generated hearing data to the applicant terminal 2. The applicant terminal 2 receives the hearing data and displays it on its own display unit.

[0015] The computer 10 acquires response data to the hearing data (step S3). The applicant terminal 2 accepts input of response data to the hearing data (selection input (input for options included in the hearing data), direct input (input using text, images (video, still images, etc.), voice, etc.)) and transmits the accepted response data to the computer 10. The computer 10 receives the response data sent by the applicant terminal 2 and acquires the response data to the hearing data.

[0016] The computer 10 generates an application document for the job application based on the response data (step S4). The computer 10 generates an application document for the job application form using a large-scale language model based on the acquired response data. The computer 10 outputs the generated application document to the applicant terminal 2. The applicant terminal 2 receives the application document and displays it on its own display unit.

[0017] The above is an overview of the processing steps executed by the application form preparation system 1. According to the present application preparation system 1, it is possible to actively suggest appropriate questions to the applicant, thereby enabling the applicant to prepare an application form that is more likely to be accepted.

[0018] [Device configuration] 2 is a block diagram showing the configuration of application form preparation system 1. The device configuration of application form preparation system 1 will be described with reference to FIG. The application preparation system 1 is a system for preparing application forms that is composed of at least a computer 10 with server functionality. In this embodiment, in addition to the computer 10, the application preparation system 1 is a system that includes an applicant terminal 2 used by the applicant and an application guidelines DB 3 in which application guidelines data is registered. The application form preparation system 1 is a system in which a computer 10 is connected to an applicant terminal 2 and an application guidelines DB 3 so as to be able to communicate data with each other via a network 8 such as a public line network or an intranet. Here, the applicant terminal 2 is connected to the application guidelines DB 3 so as to be able to communicate data with each other via the network 8. In addition, the application form preparation system 1 may include other terminals and devices in addition to the applicant terminal 2, application guidelines DB 3, and computer 10, and the number, type, and functions thereof are not particularly limited and can be designed as appropriate.

[0019] The computer 10 has a server function and may be realized, for example, by a single computer, or may be realized by multiple computers, such as a cloud computer. The computer 10 has a control unit including a CPU (Central Processing Unit), GPU (Graphics Processing Unit), RAM (Random Access Memory), ROM (Read Only Memory), etc., and a communication unit including a device for enabling communication with other terminals and devices, an application guidelines data acquisition unit for acquiring application guidelines data that shows the application guidelines in writing, and a response data acquisition unit for acquiring response data to the hearing data. The computer 10 includes a data storage unit such as a hard disk, semiconductor memory, recording medium, or memory card as a memory unit. The computer 10 includes, as processing units, various devices that perform various processes, a hearing data generation unit that generates hearing data from application guidelines data, and a document generation unit that generates application documents for application forms based on response data.

[0020] In computer 10, the control unit loads a specified program and, in cooperation with the communication unit, realizes an application guidelines data acquisition module, a hearing data output module, a response data acquisition module, an application document output module, and a recruitment result acquisition module. In addition, in the computer 10, the control unit reads a predetermined program, and in cooperation with the processing unit, realizes a hearing data generation module, an application document generation module, a judgment module, a learning module, and an update module.

[0021] The applicant terminal 2 is a terminal device used by the applicant, such as a mobile phone, smartphone, tablet terminal, laptop computer, personal computer, etc. The number, type, and functions of the applicant terminal 2 are not particularly limited and can be designed as appropriate. The applicant terminal 2 includes a CPU, GPU, RAM, ROM, etc. as a terminal control unit, and includes a device, etc. as a communication unit, for enabling communication with other terminals, devices, etc. The applicant terminal 2 includes, as an input / output unit, various devices for receiving predetermined inputs and inputting / outputting various data.

[0022] In the applicant terminal 2, the terminal control unit reads a predetermined program, and in cooperation with the communication unit, realizes an acquisition module, a transmission module, and a reception module. In addition, in applicant terminal 2, the terminal control unit reads a predetermined program, thereby realizing a display module and a reception module in cooperation with the input / output unit.

[0023] The application guidelines DB 3 is a DB managed by a computer having a predetermined server function, and is a DB in which application guidelines data, which indicates application guidelines such as application targets, application period, and application conditions in writing, is registered.

[0024] Below, each process executed by the application form preparation system 1 will be explained together with the process executed by each module. In this specification, each module may execute its processing content as its own function, or may execute its processing content via a predetermined application.

[0025] [Hearing data generation process executed by application creation system 1] The hearing data generation process executed by the application preparation system 1 will be described with reference to Figure 3. This figure shows a flowchart of the hearing data generation process executed by the applicant terminal 2 and the computer 10. This hearing data generation process shows details of the application guidelines data acquisition process (step S1) that acquires application guidelines data that shows the application guidelines in writing, and the hearing data generation process (step S2) that generates hearing data from the application guidelines data.

[0026] The acquisition module acquires application guidelines data that shows application guidelines in writing (step S10). The application guidelines include application targets, application periods, application conditions, etc. when applying for grants, subsidies, grants, etc. The application guidelines data is data that shows these application guidelines in writing. The applicant terminal 2 accepts input of application guidelines that the applicant intends to apply for, and accesses the application guidelines DB 3 that manages application guidelines data showing these application guidelines in writing. The acquisition module acquires the relevant application guidelines data from the accessed application guidelines DB3.

[0027] The transmission module transmits the application guidelines data (step S11). The transmission module transmits the application guidelines data acquired from the application guidelines DB 3 to the computer 10 .

[0028] The application guidelines data acquisition module acquires application guidelines data (step S12). The application guidelines data acquisition module receives the application guidelines data sent by the applicant terminal 2 and acquires the application guidelines data that shows the application guidelines in writing.

[0029] The computer 10 may be configured to acquire application guidelines data not only from the applicant terminal 2 but also from the application guidelines DB 3. In this case, the computer 10 acquires data, etc. related to the application guidelines for which the applicant is applying from the applicant terminal 2, etc., and accesses the application guidelines DB3, which manages the application guidelines data corresponding to the acquired data, etc. The application guidelines data acquisition module simply acquires the relevant application guidelines data from the accessed application guidelines DB3.

[0030] The hearing data generation module generates hearing data (step S13). The interview data is the content of questions posed to the applicant. The interview data includes not only basic information about the applicant company to which the applicant belongs (industry, size, capital, sales, number of employees, details of the new business (differences in manufacturing methods, differences in sales destinations), etc.), but also more detailed analytical information about the applicant company (strengths, weaknesses, opportunities, threats). For example, the interview data for basic information may consist only of a question such as "What is your company's industry?", or may include a question such as "What is your company's industry? Is it manufacturing? Is it construction? Is it transportation?" and options that can be answers to the question. Furthermore, the interview data for analytical information may consist only of a question such as "What are your company's unique strengths?", or may include a question and options that can be answers to the question. The hearing data generation module generates hearing data from the acquired application guidelines data using a large-scale language model. The large-scale language model may be based on learning results (learning results using machine learning, deep learning, etc.) of past application guidelines and hearing data for those past application guidelines, or it may be independent of the learning results of the application guidelines. When the hearing data generation module uses a large-scale language model that is independent of the learning results of the application guidelines, it only needs to generate hearing data based on the content required for the acquired application guidelines data. The large-scale language model may be operated by computer 10, or it may be operated by a device other than computer 10, such as a specified external computer. When computer 10 operates a large-scale language model, the hearing data generation module generates hearing data by inputting the application guidelines data acquired this time into this large-scale language model and acquiring hearing data as the output result. When an external computer other than computer 10 operates the large-scale language model, the hearing data generation module transmits the acquired application guideline data to the external computer. The external computer receives this application guideline data, inputs the received application guideline data into the large-scale language model, and transmits the output result as hearing data to computer 10. The hearing data generation module generates hearing data by receiving this hearing data. The hearing data generated by the hearing data generation module may be data of the required number and type according to the application guidelines data, and the content of the data is not particularly limited. Furthermore, the hearing data generated by the hearing data generation module may not only be data according to the application guidelines data, but may also include error messages when the applicant does not meet the application guidelines. In this case, the hearing data generation module may link the options or input content that do not meet the application guidelines with the error messages.

[0031] The above is the hearing data generation process.

[0032] [Response data acquisition process executed by application creation system 1] The response data acquisition process executed by the application form preparation system 1 will be described with reference to Fig. 4. This figure shows a flowchart of the response data acquisition process executed by the applicant terminal 2 and the computer 10. This response data acquisition process is a detailed explanation of the response data acquisition process (step S3) that acquires response data to the hearing data.

[0033] The hearing data output module outputs the hearing data (step S20). The hearing data output module transmits the generated hearing data to the applicant terminal 2.

[0034] The receiving module receives the hearing data (step S21). The receiving module receives the hearing data output by the computer 10 .

[0035] The display module displays the received hearing data (step S22). The display module displays the received hearing data via a predetermined UI (User Interface). The display module displays the hearing data in, for example, a chatbot format.

[0036] The reception module receives input of response data (step S23). The response data is the applicant's response to the hearing data. The reception module accepts input of response data by receiving selection input from the applicant for options included in the hearing data, and by receiving direct input from the applicant using text, images (videos, still images, etc.), voice, etc., into a specified input form.

[0037] The transmission module transmits the response data (step S24). The transmission module transmits the response data received from the applicant to the computer 10.

[0038] The response data acquisition module acquires the response data (step S25). The response data acquisition module receives the response data sent by the applicant terminal 2 and acquires the response data.

[0039] Examples of screens displayed on applicant terminal 2 during the response data acquisition process will be described with reference to Figures 5 to 12. In each figure, Figures 5 to 10 show UI 20, Figure 11 shows UI 30, and Figure 12 shows UI 40.

[0040] First, the case where the hearing data includes options will be described with reference to FIGS. The display module displays the first hearing data (question 21 and options 22 (answers 22a-d)) sent by the computer 10 as utterances from the chatbot on the UI 20 (see FIG. 5). The display module displays "What is your company's industry?" as the question 21, and displays "Please select your company's industry from the menu. Answer (manufacturing) 22a, Answer (construction) 22b, Answer (transportation) 22c, Answer (other) 22d" as the answer options 22 to this question 21. The reception module receives a tap input or the like for any of the answers 22a to 22d in the options 22, and receives input of answer data. The transmission module transmits the received response data to the computer 10, and the display module displays the received response data as a comment from the applicant on the UI 20 (see FIG. 6). For example, if the reception module receives a selection input for response 22c, the display module displays response 23 as a comment from the applicant below the option 22. Note that if there is insufficient space below the option 22 to display the comment from the applicant, the display module may transition the UI 20 downward and display at least response 23 in a displayable state. Next, the display module displays the second hearing data (question 24 and options 25 (answers 25a to 25d)) sent by the computer 10 as a utterance from the chatbot on the UI 20 (see FIG. 7). The display module displays "How much is your capital?" as question 24, and displays "Please select your company's capital from the menu. Answer (300 million yen or more) 25a, Answer (100 million yen or more but less than 300 million yen) 25b, Answer (50 million yen or more but less than 100 million yen) 25c, Answer (other) 25d" as options 25 for the answer to question 24. Note that if there is insufficient space below answer 23 to display the utterance from the chatbot, the display module may shift the UI 20 downward to display at least question 24 and options 25 in a visible state. The reception module receives a tap input or the like for any of the answers 25a to 25d in the options 25, and receives input of answer data. The transmission module transmits the received response data to the computer 10, and the display module displays the received response data as a comment from the applicant on the UI 20 (see FIG. 8). For example, when the reception module receives a selection input for response 25a, the display module displays response 26 as a comment from the applicant below the options 25. Note that if there is insufficient space below the options 25 to display the comment from the applicant, the display module may transition the UI 20 downward and display at least response 26 in a state where it can be displayed. Even if there is further hearing data, the applicant terminal 2 executes the same process, accepts input of response data for all the hearing data, and transmits the accepted response data to the computer 10.

[0041] Here, the case where the applicant does not meet the application requirements will be described with reference to FIGS. For example, a case will be described in which the application guidelines limit the applicant's industry to manufacturing, construction, or transportation, and the reception module receives input of answer 22d in option 22. The transmission module transmits the received response data to the computer 10, and the display module displays the received response data as a comment from the applicant on the UI 20 (see FIG. 9). The display module displays the answer 27 as a comment from the applicant below the options 22. If there is insufficient space to display the comment from the applicant below the options 22, the display module may transition the UI 20 downward and display at least the answer 27 in a state where it can be displayed. Next, the display module displays an error message 28 pre-linked to the answer 22d as a utterance from the chatbot on the UI 20 (see FIG. 10). The display module displays the error message 28 as "Sorry, your company's industry does not meet the application requirements for this job, so you cannot apply." Thereafter, the display module may again accept input for the option 22, or may display a message or the like urging the user to end the acceptance of input of answer data.

[0042] Next, a case where the hearing data does not include options will be described with reference to FIG. The display module displays the third hearing data (question 31) sent by the computer 10 as a utterance from the chatbot on the UI 30. The display module displays, as question 31, "When was your company established?" The reception module receives text input, voice input, etc. in the input form 37, and receives input of answer data. The transmission module transmits the received response data to the computer 10, and the display module displays the received response data as a comment from the applicant on the UI 30. The display module displays the answer 32 as a comment from the applicant below the options 22. Note that if there is insufficient space to display the comment from the applicant below the question 31, the display module may transition the UI 30 downward and display at least the answer 32 in a state where it can be displayed. Next, the display module displays the fourth hearing data (question 33) sent by the computer 10 as a utterance from the chatbot on the UI 30. The display module displays, as question 33, "Where is your business located?" The reception module receives text input, voice input, etc. in the input form 37, and receives input of answer data. The transmission module transmits the received response data to the computer 10, and the display module displays the received response data as a comment from the applicant on the UI 30. The display module displays the answer 34 as a comment from the applicant below the question 33. If there is insufficient space below the question 33 to display the comment from the applicant, the display module may transition the UI 30 downward and display at least the answer 34 in a state where it can be displayed. Next, the display module displays the fifth hearing data (question 35) sent by the computer 10 as a utterance from the chatbot on the UI 30. The display module displays "What is your main business?" as question 35. The reception module receives text input, voice input, etc. in the input form 37, and receives input of answer data. The transmission module transmits the received response data to the computer 10, and the display module displays the received response data as a comment from the applicant on the UI 30. The display module displays the answer 36 as a comment from the applicant below the question 35. If there is insufficient space below the question 35 to display the comment from the applicant, the display module may transition the UI 30 downward and display at least the answer 36 in a state where it can be displayed. Even if there is further hearing data, the applicant terminal 2 executes the same process, accepts input of response data for all the hearing data, and transmits the accepted response data to the computer 10.

[0043] Finally, another case where the hearing data does not include options will be described with reference to FIG. The display module displays, in the UI 40, a question (question about the strengths of the applicant company) 41 regarding the analytical information in the hearing data sent by the computer 10 as a utterance from the chatbot. The display module displays, as question 41, "What are the unique strengths of your company?" The reception module receives text input, voice input, etc. in the input form 43, and receives input of answer data. The transmission module transmits the received response data to the computer 10, and the display module displays the received response data as a comment from the applicant on the UI 40. The display module displays the answer 42 as a comment from the applicant below the question 41. If there is insufficient space below the question 41 to display the comment from the applicant, the display module transitions the UI 40 downward and displays at least the answer 42 in a state where it can be displayed.

[0044] This completes the response data acquisition process.

[0045] [Application document generation process executed by application creation system 1] The application document generation process executed by the application creation system 1 will be described with reference to Figure 13. This figure shows a flowchart of the application document generation process executed by the applicant terminal 2 and the computer 10. This application document generation process is a detailed description of the document generation process (step S4) that generates an application document for an application based on response data.

[0046] The application document generation module generates an application document for the job application based on the response data (step S30). The application document may be one that conforms to the application form format in the application guidelines data. This application document is generated based on response data to the acquired interview data. The format of the application document is not particularly limited, and may be one that is based on the application guidelines data. The response data is based on the answers selected and accepted by the applicant terminal 2 to questions about basic information, the answers inputted and accepted by the applicant terminal 2 to questions about basic information, and the answers inputted and accepted by the applicant terminal 2 to questions about analytical information (such as questions about the strengths of the applicant company). The application document generation module generates an application document using a large-scale language model for the acquired response data. The large-scale language model may be based on learning results (learning results using machine learning, deep learning, etc.) of previously generated application documents and responses reflected in the application document, or it may be independent of the learning results of the application document. When the application document generation module uses a large-scale language model that is independent of the learning results of the application document, the application document can be generated by applying the acquired response data to the corresponding content of the application document. The large-scale language model may be operated by computer 10, or may be operated by a device other than computer 10, such as a specified external computer. When computer 10 operates a large-scale language model, the application document generation module generates an application document by inputting the currently acquired response data into this large-scale language model and obtaining an application document as the output result. When an external computer other than computer 10 operates the large-scale language model, the application document generation module transmits the acquired response data to the external computer. The external computer receives this response data, inputs the received response data into the large-scale language model, and transmits the output result as an application document to computer 10. The application document generation module generates the application document by receiving this application document. For example, based on answers 32, 34, and 36 shown in Figure 11, we can generate an application document stating, "●Company Overview Our company was established in August 1956 and is primarily engaged in four businesses: a taxi business centered around Yatsushiro City; chartered buses used for group trips, school events, weddings, funerals, etc.; an express bus business connecting Yatsushiro City with Aso Kumamoto Airport and the Driver's License Center; and a travel business that organizes and plans tours departing and arriving in Yatsushiro." The application documents generated by the application document generation module may contain the required number and type of data in accordance with the application guidelines data and response data, and the content of the documents is not particularly limited. Furthermore, the application documents generated by the application document generation module may contain not only documents in accordance with the application guidelines data and response data, but also error messages for deficiencies in the application documents. In this case, the application document generation module may associate the deficiencies with the error messages.

[0047] Here, a case where the application document generation module generates an application document related to analysis information, particularly an application document related to strengths, will be described. The application document generation module generates an application document regarding the strengths of the applicant company using a large-scale language model for the strengths of the applicant company in the acquired response data. The large-scale language model may be based on the learning results (learning results using machine learning, deep learning, etc.) of previously generated application documents regarding strengths and the strengths of the applicant company reflected in the application document, or it may be independent of the learning results of the application document regarding strengths. When the application document generation module uses a large-scale language model that is not dependent on the learning results of the application document regarding strengths, it can generate the application document regarding strengths by, for example, applying the acquired strengths of the applicant company to the corresponding content of the application document regarding strengths. The large-scale language model may be operated by computer 10, or it may be operated by a device other than computer 10, such as a specified external computer. When computer 10 operates a large-scale language model, the application document generation module inputs the strengths of the applicant company in the response data acquired this time into this large-scale language model, and generates an application document regarding strengths by obtaining an application document regarding strengths as the output result. When an external computer other than computer 10 operates the large-scale language model, the application document generation module transmits the strengths of the applicant company in the acquired response data to the external computer. The external computer receives the strengths of the applicant company in this response data, inputs the strengths of the applicant company in the received response data into the large-scale language model, and transmits the output result to computer 10 as an application document regarding strengths. By receiving this application document regarding strengths, the application document generation module generates an application document regarding strengths. For example, based on answer 42 shown in Figure 12, the application document generation module generates an application document regarding the strengths, such as "[Strengths] Strong trust from local residents (founded 66 years ago) Attitude towards addressing local issues (collaboration with Yatsushiro City) Attitude of the entire company to take on new challenges." The application document regarding strengths generated by the application document generation module may contain the necessary number, type, etc. of data according to the strengths of the applicant company in the response data, and its content is not particularly limited. Furthermore, the application document regarding strengths generated by the application document generation module may not only correspond to the strengths of the applicant company in the response data, but may also include error messages for deficiencies in the application document, etc. In this case, the application document generation module may simply link the deficiencies, etc. with the error messages. In addition, when the application document generation module generates an application document regarding analysis information, it is not limited to an application document regarding strengths, but may also be an application document regarding weaknesses, opportunities, threats, or any other application document.

[0048] The application document output module outputs the application document (step S31). The application document output module sends the generated application document to the applicant terminal 2.

[0049] The receiving module receives the application document (step S32). The receiving module receives the application document output by the computer 10 .

[0050] The display module displays the application document (step S33). The display module displays the received application document. Here, the display module may be configured to be able to accept input from the applicant and to correct or modify the application document generated by the computer 10. In addition to displaying the received application document, the applicant terminal 2 may also convert it into a predetermined format (document format, spreadsheet format, PDF (Portable Document Format)) or output it to a printer or the like connected to the applicant terminal 2 for data communication and print the application document. It should be noted that the computer 10, rather than the applicant terminal 2, may be configured to convert the application document into a predetermined format.

[0051] The above is the application document generation process.

[0052] [Learning process executed by application creation system 1] The learning process executed by the application form preparation system 1 will be described with reference to Fig. 14. This figure shows a flowchart of the learning process executed by the applicant terminal 2 and the computer 10.

[0053] The reception module receives input of the employment results of the application form (step S40). The adoption result is the examination result (adopted or rejected, etc.) when the application document generated by the above-described application document generation process is actually submitted. The reception module accepts input of the acceptance result of the application form via a specified UI by accepting a selection input of whether or not the application form has been accepted, and by accepting direct input from the applicant using text, images, voice, etc. into a specified input form.

[0054] The transmission module transmits the application form and the employment result (step S41). The transmission module transmits the generated application form and the employment results of the accepted application form to the computer 10.

[0055] The employment result acquisition module acquires the application form and employment result (step S42). The employment result acquisition module receives the application form and employment result sent by the applicant terminal 2, and acquires the application form and employment result.

[0056] The decision module determines whether or not the application has been accepted (step S43). The determination module determines whether the obtained adoption result is adoption or not. If the determination module determines that the acquired adoption result is not adoption, that is, rejection (step S43 NO), the computer 10 ends the learning process. In this case, computer 10 can also be configured to generate measures to increase the likelihood of adoption, such as suggestions for improvements to the application form, using a large-scale language model. The large-scale language model may be based on learning results (learning results using machine learning, deep learning, etc.) of accepted applications from previously generated applications, or may be independent of learning results of accepted applications. For example, computer 10 inputs the currently acquired application form into the large-scale language model and obtains suggestions for improvements to the application form as output results, thereby generating measures to increase the likelihood of adoption, such as suggestions for improvements to the application form.

[0057] On the other hand, if the determination module determines that the acquired employment result is adoption (YES in step S43), the learning module learns the application form and the employment result for this application (step S44). Learning methods include, for example, machine learning using supervised learning, unsupervised learning, reinforcement learning, etc., as well as deep learning using convolutional neural networks, recurrent neural networks, long- and short-term memory, etc. The learning module uses a predetermined algorithm to learn from the application form obtained this time.

[0058] The update module updates the large-scale language model based on the learning result (step S45). The update module updates the large-scale language model used to generate the application form based on the learning results. The large-scale language model may be operated by the computer 10 or may be operated by a computer other than the computer 10, such as a predetermined external computer. When the computer 10 operates a large-scale language model, the update module updates the large-scale language model based on the learning results. When an external computer other than computer 10 operates the large-scale language model, the update module transmits the learning results to the external computer. The external computer receives the learning results and updates the large-scale language model based on the received learning results. In this case, computer 10 may transmit the acquired application form and hiring results to the external computer, and the external computer may execute the process of step S44. The update module may update a large-scale language model using one learning result, or may update a large-scale language model using a predetermined number of learning results.

[0059] This completes the learning process. From the next time onwards, when the computer 10 executes the process of step S30, it generates an application document for an application form using the large-scale language model updated as a result of the learning process.

[0060] The above-described means and functions are realized by a computer (including a CPU, an information processing device, and various terminals) reading and executing a predetermined program. The program may be provided, for example, from a computer via a network (Software as a Service (SaaS)) or as a cloud service. The program may also be provided in a form recorded on a computer-readable recording medium. In this case, the computer reads the program from the recording medium, transfers it to an internal or external recording device, records it, and executes it. The program may also be pre-recorded on a recording device (recording medium) and provided to the computer from the recording device via a communication line.

[0061] Although the embodiments of the present invention have been described above, the present invention is not limited to these embodiments. Furthermore, the effects described in the embodiments of the present invention are merely a list of the most preferable effects resulting from the present invention, and the effects of the present invention are not limited to those described in the embodiments of the present invention.

[0062] According to the present invention, it is possible to actively suggest appropriate questions to applicants, thereby enabling them to create application forms that are more likely to be accepted.

[0063] A first aspect disclosed in this embodiment is an application form creation system for creating an application form, an application guidelines data acquisition unit that acquires application guidelines data that show application guidelines in writing; a hearing data generation unit that generates hearing data from the application outline data; a response data acquisition unit that acquires response data to the hearing data; a document generation unit that generates an application document based on the response data; An application creation system is provided.

[0064] In a second aspect disclosed in this embodiment, the hearing data generation unit generates the hearing data using a large-scale language model for the application outline data. The present invention provides an application preparation system according to a first aspect.

[0065] A third aspect disclosed in this embodiment is such that the document generation unit generates the application document using a large-scale language model for the response data. The present invention provides an application preparation system according to a first aspect.

[0066] In a fourth aspect disclosed in this embodiment, the response data acquisition unit acquires strengths of the applicant company as the response data, the document generation unit generates the application document regarding the strengths. The present invention provides an application preparation system according to a first aspect.

[0067] A fifth aspect disclosed in this embodiment includes a learning unit that learns the job application form and the hiring results for the application; Further provided with the document generation unit generates the application document based on the learning result. The present invention provides an application preparation system according to a first aspect. [Explanation of symbols]

[0068] 1. Application Form Creation System 2. Applicant's terminal 3 Application Guidelines DB 8 Network 10. Computers 20 UI 21 questions 22 Choices 22a~d Answer 23 answers 24 questions 25 choices 25a~d Answer 26 answers 27 answers 28 Error Messages 30 UI 31 questions 32 answers 33 questions 34 answers 35 questions 36 answers 37 Input Form 40 UI 41 questions 42 answers

Claims

1. An application creation system for creating an application form, an application guidelines data acquisition unit that acquires application guidelines data that show application guidelines in writing; a hearing data generation unit that generates hearing data from the application outline data; a response data acquisition unit that acquires response data to the hearing data; a document generation unit that generates an application document based on the response data; An application creation system comprising:

2. the hearing data generation unit generates the hearing data using a large-scale language model for the application outline data; The application preparation system according to claim 1 .

3. the document generation unit generates the application document using a large-scale language model for the response data. The application preparation system according to claim 1 .

4. the response data acquisition unit acquires strengths of the applicant company as the response data, the document generation unit generates the application document regarding the strengths. The application preparation system according to claim 1 .

5. a learning unit that learns the application form and the employment results for the application; Further provided with the document generation unit generates the application document based on the learning result. The application preparation system according to claim 1 .

6. An application creation method executed by a computer that creates an application form, comprising: obtaining application guidelines data showing application guidelines in writing; generating interview data from the application guidelines data; acquiring response data to the hearing data; generating an application document for the job application based on the response data; A method for preparing an application form that includes the following.

7. The computer on which the application form is to be created A step of obtaining application guidelines data showing application guidelines in writing; generating interview data from the application guidelines data; acquiring response data to the hearing data; generating an application document for the job application based on the response data; A computer-readable program for executing the program.

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