Post matching and digital person explanation method based on talent evaluation, computer program product and talent evaluation system

Abstract

The invention provides a person-post matching and digital person explanation method based on talent evaluation, a computer program product and a talent evaluation system, and the method comprises the following steps: outputting a plurality of dimensions of evaluation questions related to talent evaluation to a user to answer, and obtaining an answer result of the user; generating multiple evaluation indexes related to the occupational quality of the user according to the answer result of the user, and inputting each evaluation index into a preset talent evaluation model to generate a talent evaluation report; matching the talent evaluation report with the occupational quality demand data of the enterprise post to obtain a person-post matching report; extracting a report key point through a large language model, and generating a digital person for explanation according to the report key point; and in the process that the digital person explains the key point of the report, if an interaction problem input by a user is received, generating interaction content corresponding to the interaction problem according to the talent evaluation report and the person-post matching report, and outputting the interaction content through the digital person.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a person-job matching and digital human explanation method based on talent assessment, a computer program product and a talent assessment system. Background Art

[0002] At present, the job market is highly competitive. When matching employees with corporate positions, traditional recruitment systems generally simply screen the basic conditions such as occupation, education, work experience, salary, etc. between employees and corporate positions, and then match them. They ignore factors such as values, personal style, and development tendency, making it difficult to match people with positions comprehensively and accurately. Moreover, after such a simple screening, there will be more matching positions, and employees need to spend time and energy to further select positions before they can find the ones that suit them. Therefore, through the traditional recruitment system, it is difficult for companies to efficiently recruit employees who match the positions, and it is difficult for employees to efficiently find the positions that suit them. Summary of the invention

[0003] The technical problem to be solved by the present invention is how to improve the accuracy and efficiency of person-job matching in a recruitment system.

[0004] In order to solve the above technical problems, the present invention provides a person-job matching and digital human explanation method based on talent assessment, comprising the following steps:

[0005] A. Output multiple dimensions of talent assessment questions to users and obtain their answers;

[0006] B. Generate multiple evaluation indicators related to the user's professional quality based on the user's answer results, input each evaluation indicator into a preset talent evaluation model, and generate a talent evaluation report with the user's professional quality data through the talent evaluation model;

[0007] C. Match the talent assessment report with the professional quality requirements of the enterprise positions to obtain a person-position matching report;

[0008] D. Input the talent assessment report and the person-job matching report into the big language model, extract the key points of the report through the big language model, and generate a digital human to explain according to the key points of the report;

[0009] E. During the process of the digital human explaining the key points of the report, if an interactive question input by the user is received, interactive content corresponding to the interactive question is generated based on the talent assessment report and the person-job matching report and outputted through the digital human.

[0010] Furthermore, in step A, the dimensions of the output evaluation questions include values, personal style, self-evaluation of abilities, development tendency, and personal strengths.

[0011] Furthermore, in the step A, before outputting the assessment questions to the user to answer, the user's basic employment information is obtained; in the step C, the user's basic employment information is also matched with the basic demand data of the enterprise position.

[0012] Furthermore, in the step E, after receiving the interactive question input by the user, the digital human pauses to explain the key points of the report.

[0013] Furthermore, in step E, if no interactive questions are received from the user, the digital human continues to explain the key points of the report.

[0014] The present invention also provides a computer program product, comprising a computer program, which implements the steps in the above method when executed by a processor.

[0015] The present invention also provides a talent assessment system, including a main control module, the main control module is connected to the user's interactive device through a server, the main control module includes a memory and a processor connected to each other, and the memory stores the above-mentioned computer program product; in the step A, multiple dimensional assessment questions related to talent assessment are output to the user for answer through the interactive device, and the user's answer results are obtained through the interactive device; in the step E, the interactive questions input by the user are received through the interactive device, and the interactive content is output through the interactive device.

[0016] Furthermore, the interactive device is an intelligent electronic device with a real-time interactive function, and the intelligent electronic device is a mobile phone, a desktop computer, a laptop computer or a tablet computer.

[0017] The present invention has the following beneficial effects: when conducting talent assessment, multiple dimensional assessment questions related to the talent assessment are output to the user for answering, multiple evaluation indicators related to the user's professional quality are generated according to the user's answer results, and each evaluation indicator is input into a preset talent assessment model, and a talent assessment report with the user's professional quality data is generated through the talent assessment model, so that the person-job matching report obtained after matching the talent assessment report with the professional quality requirement data of the enterprise position is related to the multiple dimensional assessment questions, which can improve the accuracy of person-job matching; then, the report highlights of the talent assessment report and the person-job matching report are extracted through the large language model and a digital person is generated for explanation, and during the explanation process, corresponding interactive content can be generated for the interactive questions input by the user and output answers, which can help the user quickly understand the key points of the report and answer user questions in a timely manner, and can improve the efficiency of person-job matching. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flowchart of the person-job matching and digital human explanation method based on talent assessment. DETAILED DESCRIPTION

[0019] The present invention is further described in detail below in conjunction with specific implementation methods.

[0020] The present invention provides a talent assessment system, which includes a main control module, which is connected to a user's interactive device through a server, wherein the interactive device is an intelligent electronic device with a real-time interactive function, such as a mobile phone, a desktop computer, a laptop computer, a tablet computer, etc. The main control module includes a memory and a processor connected to each other, wherein a computer program product including a computer program is stored in the memory, and when the computer program is executed by the processor, the following is realized: Figure 1 The steps in the person-job matching and digital human explanation method based on talent assessment shown specifically include the following steps A, B, C, D, and E.

[0021] A. Output multiple dimensions of talent assessment questions to users and obtain their answers.

[0022] When using the talent assessment system, users need to first use the interactive device to input their basic employment information, including name, occupation, education, work experience, salary, etc. The main control module can then obtain the basic employment information entered by the user through the server. The main control module then outputs multiple dimension assessment questions related to talent assessment through the interactive device for the user to answer. Each dimension has multiple assessment questions. After the user answers the assessment questions on the interactive device, the main control module obtains the user's answer results through the interactive device. Among them, the dimensions of the assessment questions output through the interactive device include values, personal style, self-assessment of ability, development tendency, and own advantages.

[0023] An example of an evaluation question for the value dimension is: list multiple words that reflect different values ​​for users to choose from the words that they possess the most or admire the most; list several words selected by the user for users to sort. An example of an evaluation question for the personal style dimension is: list at least two options that reflect opposite personal styles for users to choose. An example of an evaluation question for the ability self-assessment dimension is: list multiple words that reflect different abilities for users to choose from the words that they possess the most or admire the most; list several words selected by the user for users to sort. An example of an evaluation question for the development tendency dimension is: list at least two options that reflect opposite development tendencies for users to choose. An example of an evaluation question for the own advantage dimension is: list at least two options that reflect opposite advantages for users to choose.

[0024] B. Generate multiple evaluation indicators related to the user's professional quality based on the user's answer results, input each evaluation indicator into a preset talent evaluation model, and generate a talent evaluation report with the user's professional quality data through the talent evaluation model.

[0025] After obtaining the user's answer results, the main control module generates multiple evaluation indicators related to the user's professional qualities based on the user's answer results. These evaluation indicators correspond to the various dimensions of the evaluation questions, including evaluation indicators of the value dimension, evaluation indicators of the personal style dimension, evaluation indicators of the ability self-assessment dimension, evaluation indicators of the development tendency dimension, and evaluation indicators of the own advantage dimension. Then the main control module inputs each evaluation indicator into the preset talent evaluation model. The talent evaluation model generates a talent evaluation report with the user's professional quality data based on the user's multiple different dimensional evaluation indicators related to the professional quality. The talent evaluation report combines the user's values, personal style, ability self-assessment, development tendency, and own advantages to give the user a suitable position type.

[0026] C. Match the talent assessment report with the professional quality requirement data of the enterprise positions to obtain a person-job matching report.

[0027] After obtaining the talent assessment report, the main control module obtains the recruitment positions of each company and the basic demand data and professional quality demand data of the company positions from the recruitment system, and then matches the user's basic employment information with the basic demand data of each company position, matches the talent assessment report with the professional quality demand data of the company position, and selects several company positions that are most suitable for the user based on the two matching results to form a person-position matching report. The person-position matching report lists the matching degree between the user's basic employment information and the basic demand data of each company position, as well as the matching degree between the talent assessment report and the professional quality demand data of the company position. In this way, the person-position matching report obtained after matching the talent assessment report with the professional quality demand data of the company position is related to the evaluation questions of multiple dimensions, which can improve the accuracy of person-position matching.

[0028] D. Input the talent assessment report and the person-job matching report into the big language model, extract the key points of the report through the big language model, and generate a digital human to explain based on the key points of the report.

[0029] After obtaining the person-job matching report, the main control module inputs both the talent assessment report and the person-job matching report into the large language model, extracts the report highlights of the talent assessment report and the person-job matching report through the large language model, and then generates a digital human to explain based on the report highlights of the two.

[0030] It should be noted that a large language model refers to a deep learning model trained with a large amount of text data, which can generate natural language text or understand the meaning of language text. A large language model can handle a variety of natural language tasks, such as text classification, question and answer, dialogue, and text extraction. A digital human refers to a virtual character image constructed with reference to a real person.

[0031] E. During the process of the digital human explaining the key points of the report, if an interactive question is received from the user, the interactive content corresponding to the interactive question will be generated based on the talent assessment report and the person-job matching report and output through the digital human.

[0032] When the digital human is explaining the key points of the report, the main control module detects in real time through the interactive device whether the interactive questions input by the user are received. If no interactive questions input by the user are received, the digital human continues to explain the key points of the report. If interactive questions input by the user are received through the interactive device, the digital human is first ordered to pause explaining the key points of the report, and then the interactive content that can answer the user's questions is identified in the talent assessment report and the person-job matching report based on the user's interactive questions, and then the interactive content corresponding to the interactive questions is generated according to the talent assessment report and the person-job matching report, and the answers are output through the digital human. This can help users quickly understand the key points of the report and answer user questions in a timely manner, thereby improving the efficiency of person-job matching.

[0033] The above is only an implementation method of the invention, and does not limit the scope of patent protection. Those skilled in the art can make non-substantial changes or substitutions based on the invention, which still fall within the scope of patent protection.

Claims

1. A method for matching people with positions and explaining digital people based on talent assessment, characterized in that: The steps include: A. Output multiple dimensions of talent assessment questions to users and obtain their answers; B. Generate multiple evaluation indicators related to the user's professional quality based on the user's answer results, input each evaluation indicator into a preset talent evaluation model, and generate a talent evaluation report with the user's professional quality data through the talent evaluation model; C. Match the talent assessment report with the professional quality requirements of the enterprise positions to obtain a person-position matching report; D. Input the talent assessment report and the person-job matching report into the big language model, extract the key points of the report through the big language model, and generate a digital human to explain according to the key points of the report; E. During the process of the digital human explaining the key points of the report, if an interactive question input by the user is received, interactive content corresponding to the interactive question is generated based on the talent assessment report and the person-job matching report and outputted through the digital human.

2. The method for matching people with positions and explaining digital people based on talent assessment according to claim 1 is characterized in that: In step A, the dimensions of the output evaluation questions include values, personal style, self-evaluation of abilities, development tendency, and personal strengths.

3. The method for matching people with positions and explaining digital people based on talent assessment according to claim 1 is characterized in that: In the step A, the basic employment information of the user is obtained before the assessment questions are output to the user for answering; in the step C, the basic employment information of the user is also matched with the basic demand data of the enterprise positions.

4. The method for matching people with positions and explaining digital people based on talent assessment according to claim 1 is characterized in that: In the step E, after receiving the interactive question input by the user, the digital human pauses to explain the key points of the report.

5. The method for matching people with positions and explaining digital people based on talent assessment according to claim 1 is characterized in that: In the step E, if no interactive questions are received from the user, the digital human continues to explain the key points of the report.

6. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps in the method according to any one of claims 1 to 5 are implemented.

7. A talent assessment system, characterized in that: The main control module comprises a main control module, which is connected to the user's interactive device through a server, and the main control module comprises a memory and a processor connected to each other, and the computer program product according to claim 6 is stored in the memory; in the step A, multiple dimensional assessment questions related to talent assessment are output to the user for answer through the interactive device, and the user's answer results are obtained through the interactive device; in the step E, the interactive questions input by the user are received through the interactive device, and the interactive content is output through the interactive device.

8. The talent assessment system according to claim 7, characterized in that: The interactive device is an intelligent electronic device with a real-time interactive function, and the intelligent electronic device is a mobile phone, a desktop computer, a laptop computer or a tablet computer.

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