Recruitment systems, recruitment methods, and programs

Abstract

To improve matching accuracy. [Solution] A personnel referral system that refers to the response history of a first question and a first answer to the first question received from personnel, including the questioner, and introduces personnel who have knowledge related to a second question received from the questioner, comprising: a registration unit that registers the response history of a first question and a first answer generated in response to the first question in the past, linked to the personnel; an evaluation unit that evaluates the attributes of the personnel based on the response history; a reception unit that receives a second question from the questioner; an identification unit that refers to the evaluation of the attributes of the personnel and identifies personnel who have knowledge related to the second question from the personnel linked to the response history; a generation unit that generates a second answer to the second question and an introduction text of the identified personnel as a response to the second question; and an output unit that outputs the generated response.

Description

Technical Field

[0001] The present invention relates to a technology effective for talent matching. Background Art

[0002] Conventionally, matching techniques based on various methods have been provided. For example, Patent Document 1 discloses, as a talent matching technique, a technology for performing matching by comparing information from the recruiting side and the job-seeking side when deploying talent or selecting project personnel. Prior Art Documents Patent Documents

[0003] Patent Document 1 Japanese Unexamined Patent Publication No. 2025-180753 Summary of the Invention Problem to be Solved by the Invention

[0004] Conventional matching techniques like the technology described in Patent Document 1 perform matching based on talent information such as the talents' skills and achievements. For this reason, the accuracy of talent information and evaluation criteria do not necessarily match between an applicant desiring matching and a subject to be matched.

[0005] Further, since the relationship between the applicant and the subject is based on talent information, the relevance between the applicant and the subject is not taken into consideration. In addition, the lack of consideration for relevance also causes the problem that an applicant and a subject that are actually effective for matching are not matched with each other.

[0006] Therefore, there is a need for a technology that improves matching accuracy by taking into consideration the relevance between an applicant and a subject.

[0007] The present invention aims to provide a talent introduction system, talent introduction method, and program that can improve matching accuracy by considering the relationship between those who wish to be matched and those who are the target of the match. [Means for solving the problem]

[0008] The present invention provides a personnel referral system that refers to a history of responses to a first question and a first answer to the first question received from personnel, including questioners, and introduces personnel who have knowledge related to a second question received from a questioner, comprising: a registration unit that registers the history of responses to a first question and a first answer generated in response to the first question in the past, linked to the personnel; an evaluation unit that evaluates the attributes of the personnel based on the response history; a reception unit that receives a second question from the questioner; an identification unit that refers to the evaluation of the attributes of the personnel and identifies personnel who have knowledge related to the second question from the personnel linked to the response history; a generation unit that generates a second answer to the second question and an introduction text of the identified personnel as a response to the second question; and an output unit that outputs the generated response.

[0009] According to the present invention, by introducing individuals with knowledge relevant to the questioner's question based on each individual's response history, it becomes possible to match the questioner with individuals while considering their relationship to the questioner. As a result, it becomes possible to improve the accuracy of the matching.

[0010] Although this invention falls under the category of systems, similar functions and effects can be achieved in other categories such as methods and programs. [Effects of the Invention]

[0011] According to the invention, it becomes possible to improve matching accuracy. [Brief explanation of the drawing]

[0012] [Figure 1] This is a diagram illustrating the overview of the personnel placement system 1. [Figure 2] This diagram shows the functional configuration of the personnel placement system 1. [Figure 3] This diagram shows a flowchart of the attribute evaluation process performed by computer 10. [Figure 4] This diagram shows a flowchart of the personnel recruitment process performed by computer 10. [Modes for carrying out the invention]

[0013] Hereinafter, embodiments for carrying out the invention will be described in detail with reference to the attached drawings. In the following drawings, the same elements are denoted by the same numbers or reference numerals throughout the description of the embodiments.

[0014] In this specification, "generative AI" generally refers to generative artificial intelligence technology that generates new data or content (not limited to text, but including images, videos, programs, etc.) based on given input data, and may be implemented using technology that utilizes language models.

[0015] [Overview of Recruitment System 1] Refer to Figure 1 to explain the overview of the recruitment system 1. This figure is a schematic diagram illustrating the overview of the recruitment system 1.

[0016] The personnel referral system 1 is a system consisting of at least a computer 10 that has server functionality, refers to the response history of the first question and the first answer to the first question received from personnel including the questioner, and refers to personnel who have knowledge related to the second question received from the questioner. In this embodiment, in addition to the computer 10, the personnel referral system 1 includes an information terminal 3 used by personnel including the questioner who asks questions to the generating AI.

[0017] The information terminal 3 is a terminal device used by human resources including a questioner who asks questions, and is, for example, a terminal device such as a mobile phone, a smartphone, a tablet terminal, a personal computer, or a laptop computer, or a wearable terminal such as a smart watch, smart glasses, or an HMD (Head Mounted Display). The number of the information terminals 3 can be appropriately designed according to the number of human resources.

[0018] The computer 10 has a server function, and may be implemented by, for example, a single computer, or may be implemented by a plurality of computers like a cloud computer.

[0019] The cloud computer in the present specification may be either one that scalably uses any computer when performing a specific function, or one that includes a plurality of functional modules for realizing a certain system and uses the functions by freely combining them.

[0020] Note that the human resource introduction system 1 may include other terminals, devices and the like in addition to the information terminal 3 and the computer 10 described above, and the number, type and functions thereof are not particularly limited and can be appropriately designed.

[0021] An overview of processing steps when the human resource introduction system 1 refers to the response history of the first question received from human resources including the questioner and the first answer to the first question, and introduces human resources having knowledge related to the second question received from the questioner will be described.

[0022] The computer 10 registers, in association with the human resources, the response history of the first question received from the human resources in the past and the first answer generated for the first question (step S1).

[0023] Computer 10 receives questions from personnel, including the questioner described later, via a predetermined UI (User Interface) displayed on the information terminal 3. Computer 10 inputs the received questions into the generating AI, causes the generating AI to generate answers to the questions, and generates the answers. Computer 10 displays the generated answers on the information terminal 3 via the predetermined UI.

[0024] Computer 10 registers the response history of received questions and generated answers, linking them to the person who asked the question.

[0025] Computer 10 evaluates the attributes of the personnel based on the response history (step S2).

[0026] Computer 10 inputs the response history into the generating AI, and has the generating AI evaluate the attributes of the personnel based on this response history. Computer 10 then registers the attribute evaluation for the personnel whose response history has been registered.

[0027] Computer 10 receives the second question from the questioner (step S3).

[0028] Computer 10 receives the question from the questioner via a predetermined UI displayed on the information terminal 3.

[0029] Computer 10 refers to an evaluation of the personnel attributes and identifies personnel who have knowledge related to the second question from the personnel linked to the response history (step S4).

[0030] Computer 10 inputs the received question, the registered questioner's attribute evaluation, and the registered attribute evaluation of other personnel into the generating AI to identify personnel who possess knowledge related to the received question.

[0031] Computer 10 generates a second answer to the second question and a description of the identified person as a response to the second question (step S5).

[0032] Computer 10 inputs the received question into the generating AI, causing the generating AI to generate an answer to the question, and then generates the answer. Computer 10 generates a description of the identified person. Computer 10 combines these answers and the description to generate a response.

[0033] Computer 10 outputs the generated response (step S6).

[0034] Computer 10 displays the generated response on information terminal 3 via a predetermined UI.

[0035] The above is an overview of the personnel placement system 1.

[0036] According to the talent referral system 1, by referring individuals with knowledge related to the questioner's question to the questioner based on the response history of the individuals, including the questioner, it becomes possible to match the questioner with individuals that take into account their relationship to the questioner, thereby improving the accuracy of the matching.

[0037] Referring to Figure 2, the device configuration of the personnel placement system 1 will be explained. The figure is a block diagram showing the device configuration of the personnel placement system 1.

[0038] The personnel referral system 1 consists of a computer 10 that refers to the response history of the first question and the first answer to the first question received from personnel, including the questioner, and refers to personnel who have knowledge related to the second question received from the questioner.

[0039] In this embodiment, the personnel referral system 1 is a system that further includes an information terminal 3 used by each personnel, including the questioner, in addition to the computer 10.

[0040] The personnel placement system 1 is a system in which a computer 10 is connected to an information terminal 3 via a network 8, such as an open network like a public telephone network or a closed network like an in-house LAN, enabling data communication.

[0041] Furthermore, the personnel placement system 1 may include other terminals and devices in addition to the information terminal 3 and computer 10, and there are no particular limitations on the number, types, and functions of these devices; they can be designed as appropriate.

[0042] Information terminal 3 is the aforementioned terminal device used by personnel. Information terminal 3 includes a terminal control unit with a CPU (Central Processing Unit), GPU (Graphics Processing Unit), RAM (Random Access Memory), ROM (Read Only Memory), etc., and a communication unit with devices that enable communication with other terminals and devices. Information terminal 3 also includes an input / output unit with various devices that receive predetermined inputs and perform input / output of various data.

[0043] Computer 10 has server functionality and may be implemented using a single computer, or, like a cloud computer, using multiple computers. Computer 10 includes a control unit with a CPU, GPU, RAM, ROM, etc., and a communication unit with devices that enable communication with other terminals and devices. Computer 10 includes a storage unit with data storage using a hard disk, semiconductor memory, recording media, memory card, etc. Computer 10 includes a processing unit with various devices that perform various processes.

[0044] Computer 10, with its control unit, communication unit, memory unit, and processing unit working together, executes functions such as: a registration unit that registers the response history of the first question and the first answer generated in response to the first question, linked to the personnel; an evaluation unit that evaluates the attributes of the personnel based on the response history; a reception unit that receives the second question from the questioner; an identification unit that refers to the evaluation of the personnel's attributes and identifies personnel with knowledge related to the second question from the personnel linked to the response history; a generation unit that generates the second answer to the second question and an introduction of the identified personnel as a response to the second question; and an output unit that outputs the generated response.

[0045] The computer 10, by having the control unit load a predetermined program, works in cooperation with the communication unit to implement a question reception module, an answer output module, a referral setting reception module, a response output module, and a notification module.

[0046] Furthermore, the computer 10, in cooperation with the memory unit, realizes a registration module when the control unit reads a predetermined program.

[0047] Furthermore, the computer 10, by having the control unit read a predetermined program, works in cooperation with the processing unit to realize an answer generation module, an evaluation module, a setting module, a specific module, and a response generation module.

[0048] Computer 10 has the functionality of generative AI (such as a language model for natural language processing). Generative AI refers to AI technology that comprehensively understands and processes various data formats (text, images (still images, videos, etc.), programs, etc.). Generative AI is generally a generative artificial intelligence technology that generates new data or content (data including images, videos, programs, etc., not limited to text) based on given input data, and can be implemented, for example, by technology that utilizes a predetermined language model (such as a chatbot). Generative AI can generate new data not included in the training data by learning the regularity and structure of the training data during training. Computer 10 provides the generative AI as either on-premise generative AI (generative AI provided in a closed network environment), cloud-based generative AI (generative AI provided in an open network environment), or both.

[0049] Furthermore, the generation AI function does not necessarily have to be possessed by computer 10. In that case, a computer for generation AI, connected to computer 10 in a closed network environment or an open network environment and capable of data communication, may possess that function. In this case, the computer for generation AI may perform the functions related to generation AI that would otherwise be performed by computer 10.

[0050] The following describes each process performed by the personnel placement system 1, along with the processes performed by each module described above. In this specification, each module may perform its processing as a function it possesses, or it may perform it through a predetermined application.

[0051] [Attribute evaluation process] Referring to Figure 3, the attribute evaluation process performed by computer 10 will be explained. This figure is a flowchart of the attribute evaluation process performed by computer 10. The attribute evaluation process includes details of a registration process (step S1) in which the response history of the first question and the first answer generated in response to the first question, which has been received from the personnel in the past, is registered in association with the personnel, and an evaluation process (step S2) in which the attributes of the personnel are evaluated based on the response history.

[0052] The question reception module receives questions from personnel (step S10).

[0053] The content of the questions that the question reception module receives from candidates is not particularly limited and can be anything. Furthermore, candidates include those who ask questions in the candidate referral process described later.

[0054] Information terminal 3 receives questions from personnel via a predetermined UI. This UI is, for example, a screen that sends and receives messages between personnel and computer 10 and displays the messages in a predetermined format (such as a speech bubble) in chronological order. Information terminal 3 displays the questions as messages from personnel.

[0055] Information terminal 3 accepts questions via direct input using an input device such as a virtual keyboard or voice input into designated input fields on the UI. Information terminal 3 displays the received questions on the UI and transmits them to computer 10.

[0056] The question reception module receives this question and accepts questions from personnel.

[0057] The answer generation module generates an answer to the received question (step S11).

[0058] The content of the answers generated by the answer generation module is not particularly limited; it should be something similar to an answer to the question.

[0059] The answer generation module generates an answer generation prompt that includes the received question and a command to the AI ​​that generates an answer to this question. The method by which the answer generation module generates the answer generation prompt is not particularly limited, but for example, it may be a combination of the received question and a pre-configured command.

[0060] The answer generation module inputs the answer generation prompt to the generation AI. The answer generation module retrieves the answer generated by the generation AI based on the answer generation prompt and generates an answer to the received question.

[0061] The response output module outputs the generated response to the personnel (step S12).

[0062] The response output module sends the generated response to the information terminal 3.

[0063] Information terminal 3 receives the response and displays it via a predetermined UI. This UI is, for example, a screen that sends and receives messages between the personnel and computer 10 and displays the messages in a predetermined format (such as a speech bubble) in chronological order. Information terminal 3 displays the response as a message from computer 10.

[0064] The registration module registers the received questions and generated answers as response history, linking them to the personnel (step S13).

[0065] The response history is a record of questions and answers for each individual.

[0066] The registration module registers the questions received from personnel and the answers generated to those questions as a response history, linked to the personnel's identifier (ID, management number, name, etc.), in the personnel database (hereinafter, the database will also be simply referred to as DB). The personnel DB contains various personnel, and for each personnel, the questions received and the answers to those questions are registered. The questioners, as described later, are also registered as personnel in this personnel DB.

[0067] The evaluation module evaluates the attributes of the personnel based on their response history (step S14).

[0068] Personnel attributes refer to the person's abilities and level of ability. Abilities should at least include knowledge in a specified field (e.g., business operations (human resources, finance, sales, law), technology (IT, network, security), management (project management, quality control, etc.), languages ​​(English, Chinese, etc.), academics (mathematics, chemistry, biology, geology, physics, engineering, civil engineering, etc.)), but are not particularly limited; they should include any knowledge, skills, or characteristics of the person. Level of ability refers to an indicator of the person's abilities, and can be a score (e.g., a score out of 100), qualifications held (e.g., status of qualifications related to ability (presence or absence of relevant qualifications, qualification level, etc.)), or level of understanding (e.g., what level of understanding is achieved), but are not particularly limited; one indicator or a combination of indicators should be used to represent the person's abilities.

[0069] The evaluation module may perform the evaluation of personnel attributes when new questions and answers are registered in the personnel database, or when a predetermined number of questions and answers have been registered in the personnel database. When the evaluation module performs the evaluation of personnel attributes, it may use only newly registered questions and answers, or it may use newly registered questions and answers as well as previously registered questions and answers. When the evaluation module evaluates personnel attributes, if previous evaluations exist, it may overwrite the content with the new evaluation, or it may use a predetermined process for the previous evaluation and the new evaluation (for example, if it is a score, it may calculate the mean, median, minimum, maximum, etc. of the previous evaluation and the new evaluation and use the calculation results, and similarly for other indicators, it may be designed as appropriate). Also, when the evaluation module evaluates personnel attributes, if no previous evaluations exist, it may be configured to add the content.

[0070] The evaluation module generates an attribute evaluation prompt that includes the response history registered in the talent database and a command statement that instructs the generating AI to evaluate the attributes of the talent based on this response history. This command statement instructs the generating AI to evaluate attributes by assigning pre-set ability tags and evaluating the level of each tag (ability) based on the response history for each tag. The method by which the evaluation module generates the attribute evaluation prompt is not particularly limited, but for example, it may be a combination of the response history registered in the talent database and a pre-set command statement.

[0071] The evaluation module inputs attribute evaluation prompts to the generating AI. The evaluation module obtains the level evaluation for each tag in the response history generated by the generating AI based on the attribute evaluation prompts, and evaluates the attributes of the personnel.

[0072] The registration module registers the generated personnel evaluations, linking them to the personnel (step S15).

[0073] The registration module associates ability-related tags with the identifiers of the relevant personnel registered in the personnel database, and further associates the evaluation results of the ability levels with these tags, thereby registering the personnel evaluation. Tags that were not evaluated do not need to be registered in the personnel database.

[0074] The above describes the attribute evaluation process.

[0075] Through attribute evaluation processing, the attributes of each individual are evaluated. As a result, when a questioner asks a question, the relevant individuals can be identified by referring to the evaluation results of these attributes.

[0076] Furthermore, the talent database can also be configured to include a referral flag for each registered talent, indicating whether or not they are eligible to make a referral.

[0077] Let me explain this case.

[0078] Information terminal 3 accepts input from the individual via a predetermined UI, indicating whether they are willing to make referrals to other individuals or refusing to make referrals. This UI is not particularly limited and can be any screen that accepts input for this setting.

[0079] Information terminal 3 transmits the received settings to computer 10.

[0080] The referral setting reception module receives this setting and accepts whether the person can refer other people or refuses to be referred.

[0081] The configuration module determines whether or not to recommend personnel based on the received configuration details.

[0082] The configuration module sets the referral flag for the corresponding talent in the talent database to the "on" state if the received configuration allows for referral. Conversely, if the received configuration indicates that referral should be refused, the configuration module sets the referral flag for the corresponding talent in the talent database to the "off" state.

[0083] In the personnel referral process described later, when computer 10 attempts to identify personnel, it only identifies personnel with the referral flag turned on (personnel who have been permitted to be referred), and excludes personnel with the referral flag turned off (personnel who have been refused referral) from the identification process.

[0084] The above describes the process when the referral flag is registered.

[0085] [Recruitment processing] Referring to Figure 4, the personnel referral process performed by computer 10 will be explained. This figure is a flowchart of the personnel referral process performed by computer 10. The personnel referral process includes details of the following steps: reception process (step S3) in which the second question is received from the questioner; identification process (step S4) in which personnel with knowledge related to the second question are identified from personnel linked to the response history by referring to the evaluation of personnel attributes; generation process (step S5) in which the second answer to the second question and an introduction text for the identified personnel are generated as a response to the second question; and output process (step S6) in which the generated response is output.

[0086] The question reception module receives questions from questioners (step S20).

[0087] The content of the questions that the question receiving module accepts from questioners is not particularly limited; it can be anything.

[0088] Information terminal 3 receives questions from the questioner via a predetermined UI. This UI is, for example, a screen that sends and receives messages between the questioner and computer 10 and displays the messages in a predetermined format (such as a speech bubble) in chronological order.

[0089] Information terminal 3 accepts questions via direct input using an input device such as a virtual keyboard or voice input into designated input fields on the UI. Information terminal 3 displays the received questions on the UI and transmits them to computer 10.

[0090] The question receiving module receives this question and accepts questions from the questioner.

[0091] The specific module refers to an evaluation of the personnel attributes and identifies personnel who possess knowledge related to the received question from the personnel linked to the response history (step S21).

[0092] Knowledge related to a question is intended to be evaluated based on attributes related to the question. Specifically, it is intended that tags related to the question are registered in the talent database, and that the evaluation of the attributes corresponding to these tags is higher than that of the questioner. When a specific module identifies a talent from the talent database, it identifies the talent while excluding the questioner.

[0093] The specific module generates a personnel identification prompt that includes an instruction to identify personnel with knowledge related to the question from among the personnel linked to the response history, by referring to the evaluation of the questioner's attributes (tags and tag level evaluation) registered in the personnel database, the received question, and the attribute evaluation of each personnel registered in the personnel database excluding the questioner. This instruction causes the generating AI to identify personnel, excluding questioners whose attribute evaluations are higher than the questioner's attribute evaluation among the attribute evaluations of each personnel registered in the personnel database. This instruction may include the personnel database itself, or it may include content that temporarily grants the generating AI access to the personnel database and allows it to refer to it. The method by which the specific module generates the personnel identification prompt is not particularly limited, but for example, it may be a combination of the evaluation of the questioner's attributes registered in the personnel database, the received question, and a pre-configured instruction.

[0094] In addition, in the talent identification prompt, the evaluation of the questioner's attributes may include an evaluation of the questioner's attributes themselves, or it may include content that temporarily grants the generating AI access to the talent database and allows it to refer to the talent database.

[0095] Here, the specific module should add a command to the talent identification prompt that, if a referral flag is set in the talent database, will only identify talents with the referral flag turned on, and exclude talents with the referral flag turned off.

[0096] The specific module inputs a personnel identification prompt to the generating AI. The specific module obtains the identifier of the personnel identified by the generating AI based on the personnel identification prompt, refers to an evaluation of the personnel's attributes, and identifies personnel with knowledge related to the received question from the personnel linked to the response history.

[0097] The response generation module generates an answer to the question and a description of the identified person as a response to the question (step S22).

[0098] The response generation module generates a response generation prompt that includes the received question and a command to generate an answer to that question. This command instructs the generation AI to generate an answer to the received question.

[0099] The response generation module inputs the response generation prompt to the generation AI. The response generation module retrieves the response to the received question that the generation AI has generated based on the response generation prompt, and generates an answer to the question.

[0100] The response generation module generates a description of a person (hereinafter referred to as a "recommended person") who possesses knowledge related to the question identified by a specific module. This description may be a pre-configured description with the identifier of the recommended person incorporated into it, or it may be generated by a generation AI.

[0101] When the response generation module generates an introduction text for a candidate using a generation AI, it generates an introduction text generation prompt that includes the identifier of the candidate and a command to generate an introduction text introducing this candidate to the questioner. This command instructs the generation AI to generate an introduction text introducing the candidate to the questioner. The response generation module inputs the introduction text generation prompt to the generation AI. The response generation module retrieves the introduction text introducing the candidate to the questioner that the generation AI has generated based on the introduction text generation prompt, and generates an introduction text introducing the candidate to the questioner.

[0102] The response generation module generates a response to a question by combining the answer to the generated question with an introductory text introducing the candidate to the questioner. The response generated by the response generation module is not particularly limited as long as it is a combination of an answer and an introductory text; for example, it may be an answer to a question followed by an introductory text introducing the candidate to the questioner.

[0103] The response output module outputs the generated response to the questioner (step S23).

[0104] The response output module sends the generated response to the information terminal 3.

[0105] Information terminal 3 receives the response and displays it via a predetermined UI. This UI is similar in content to the UI displayed by information terminal 3 as described above, and is a screen that sends and receives messages between the questioner and computer 10, displaying the messages in a predetermined format (such as a speech bubble) in chronological order. Information terminal 3 displays the response as a message from computer 10.

[0106] The notification module notifies the referrer that they have been referred (step S24).

[0107] The notification module outputs a notification message to the questioner informing them that they have introduced a person to the person being introduced, who has been identified by a specific module and for whom a response generation module has generated an introduction message. The notification message may be a pre-configured notification message with the identifier of the person being introduced and the identifier of the questioner incorporated into it, or it may be generated by a generation AI.

[0108] When the notification module generates a notification message using a generation AI, it generates a notification message generation prompt that includes an identifier for the person being introduced, an identifier for the questioner, and a command to generate a notification message informing the questioner that the person being introduced has been introduced. This command instructs the generation AI to generate a notification message informing the questioner that the person being introduced has been introduced. The notification module inputs the notification message generation prompt to the generation AI. The notification module retrieves the notification message generated by the generation AI based on the notification message generation prompt and generates the notification message.

[0109] The notification module sends the generated notification message to the information terminal 3 of the referral personnel identified from the personnel database and for whom the referral message has been generated.

[0110] Information terminal 3 receives a notification message and displays it via a predetermined UI. This UI is not particularly limited and can be designed as appropriate, as long as it is a screen capable of displaying the notification message.

[0111] Furthermore, the notification message generated by the notification module only needs to inform the referrer that the referrer has been referred; the part about the person who made the referral (the questioner) can be omitted.

[0112] The above describes the process for recruiting personnel.

[0113] The talent referral process introduces candidates relevant to the questioner's question based on the history of the generation AI typically used by both the questioner and the person being referred. As a result, it becomes possible to improve the accuracy of the matching process.

[0114] The means and functions described above are realized by a computer (including the CPU, information processing unit, and various terminals) reading and executing a predetermined program. The program may be provided, for example, via a network from the computer (SaaS: Software as a Service) or as a cloud service. Alternatively, the program may 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. Alternatively, the program may be pre-recorded on a recording device (recording medium) and provided to the computer from that recording device via a communication line.

[0115] Although embodiments of the invention have been described above, the invention is not limited to the embodiments described above. Furthermore, the effects described in the embodiments of the invention are merely a list of the most preferred effects resulting from the invention, and the effects of the invention are not limited to those described in the embodiments.

[0116] A first embodiment disclosed in the embodiments provides a personnel referral system that refers to a history of responses to a first question and a first answer to the first question received from personnel, including questioners, and introduces personnel who have knowledge related to a second question received from a questioner, comprising: a registration unit that registers the history of responses to a first question and a first answer generated in response to the first question in the past, linked to the personnel; an evaluation unit that evaluates the attributes of the personnel based on the response history; a reception unit that receives a second question from the questioner; an identification unit that refers to the evaluation of the attributes of the personnel and identifies personnel who have knowledge related to the second question from the personnel linked to the response history; a generation unit that generates a second answer to the second question and an introduction text of the identified personnel as a response to the second question; and an output unit that outputs the generated response.

[0117] A second embodiment disclosed in the embodiments provides a personnel referral system according to the first embodiment, wherein the evaluation unit evaluates the personnel's abilities and the level of those abilities as attributes of the personnel.

[0118] A third embodiment disclosed in the embodiments provides a personnel referral system according to the first embodiment, further comprising a setting unit for setting whether or not to refer personnel, wherein the specifying unit specifies only personnel for whom referral is permitted and excludes personnel for whom referral is refused from the specified target.

[0119] A fourth embodiment disclosed in the embodiments provides a personnel referral system according to the first embodiment, further comprising a notification unit that notifies the person from whom the referral text was generated that they have been referred. [Explanation of Symbols]

[0120] 3 information terminals, 8 networks, 10 computers

Claims

1. A personnel referral system that refers to the response history of the first question and the first answer to the first question received from personnel, including the questioner, and introduces personnel who have knowledge related to the second question received from the questioner, A registration unit registers the response history of the first question received from the aforementioned personnel and the first answer generated in response to the said first question, linking it to the said personnel. An evaluation unit that evaluates the attributes of the personnel based on the response history, The reception area receives the second question from the aforementioned questioner, An identification unit that, by referring to the evaluation of the attributes of the aforementioned personnel, identifies personnel who possess knowledge related to the second question from among the personnel linked to the response history, A generation unit that generates a second answer to the second question and an introduction of the identified person as a response to the second question, An output unit that outputs the generated response, A recruitment system equipped with the necessary features.

2. The evaluation unit evaluates the abilities and level of those abilities of the personnel as attributes of the personnel. The personnel placement system according to claim 1.

3. A settings unit for determining whether or not to introduce personnel. Furthermore, The aforementioned identification unit will only identify individuals who have been approved for introduction, and will exclude individuals who have been refused introduction from being identified. The personnel placement system according to claim 1.

4. A notification unit that notifies the person from whom the aforementioned introduction text was generated that they have been introduced. The personnel placement system according to claim 1, further comprising the following:

5. A method for introducing personnel by a computer, which refers to the response history of the first question and the first answer to the first question received from personnel including the questioner, and introduces personnel who have knowledge related to the second question received from the questioner, The steps include registering the response history of the first question received from the aforementioned personnel and the first answer generated in response to the first question, linked to the aforementioned personnel, A step of evaluating the attributes of the person based on the response history, The first step is to receive a second question from the aforementioned questioner, The steps include: referring to the evaluation of the attributes of the aforementioned personnel, identifying personnel who possess knowledge related to the second question from among the personnel linked to the response history; The steps include generating a second answer to the second question and an introduction to the identified person as a response to the second question, The steps include outputting the generated response, A recruitment method that includes the following features.

6. The computer, by referring to the response history of the first question and the first answer to the first question received from the person asking the question, introduces a person who has knowledge related to the second question received from the person asking the question. A step of registering the response history of the first question received from the aforementioned personnel and the first answer generated in response to the said first question, linked to the said personnel. A step of evaluating the attributes of the person based on the response history, Steps to receive a second question from the aforementioned questioner, A step of referring to the evaluation of the attributes of the aforementioned personnel and identifying personnel who possess knowledge related to the second question from among the personnel linked to the response history, A step of generating a second answer to the second question and an introduction of the identified person as a response to the second question, A step of outputting the generated response, A computer-readable program for executing [something].

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