Person characteristic evaluation system, person characteristic evaluation device, person characteristic evaluation method and program

Abstract

To provide a person characteristic evaluation system, a person characteristic evaluation device, a person characteristic evaluation method, and a program for implementing the same, which can more reliably evaluate characteristics of a person and enable better personnel to be recruited and evaluated by collecting items related to characteristics of the person from routine work and the like and utilizing the items when evaluating the characteristics of the person.SOLUTION: A person characteristic evaluation system 1 includes extraction means 10 for collecting a plurality of pieces of information in which contents related to a specific person are recorded, analysis means 20 for analyzing the information collected by the extraction means 10 and quantifying and storing characteristics of the specific person for each field, and evaluation means 30 for evaluating the characteristics of the specific person based on numerical values stored by the analysis means 20.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a person characteristic evaluation system, a person characteristic evaluation device, a person characteristic evaluation method, and a program for evaluating the characteristics of a specific person. [Background technology]

[0002] Traditionally, in employment interviews (see, for example, Reference 1) and personnel evaluations, people are often evaluated based on the cases in which the person has been involved as stated in documents such as their resume, and on the way they speak during the interview. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2002-140476 Summary of the Invention [Problem to be solved by the invention]

[0004] However, with the conventional methods described above, there is a tendency for high evaluations to be given to people who have clear achievements on paper or who have excellent interview skills, and there is a risk that high evaluations will not be given to reliable people who can get things done honestly and reliably even if they do not have clear achievements, or to talented people who are actually excellent even if they do not have good interview skills.

[0005] The present invention has been made in consideration of such problems, and aims to provide a personal characteristic evaluation system, a personal characteristic evaluation device, a personal characteristic evaluation method, and a program for realizing these, which can more reliably evaluate a person's characteristics and recruit and evaluate better human resources by collecting information related to the characteristics of the person from their daily work, etc., and utilizing this information when evaluating the person's characteristics. [Means for solving the problem]

[0006] To achieve this goal, the present invention is characterized by a personal characteristic evaluation system that collects and stores information about a specific person, analyzes the collected and stored information using AI, and generates evaluation information about the specific person.

[0007] The present invention is also characterized by a personal characteristic evaluation system having an extraction means for collecting a plurality of pieces of information in which content relating to a specific person is recorded, an analysis means for analyzing the information collected by the extraction means and quantifying and saving the characteristics of the specific person for each field, and an evaluation means for evaluating the characteristics of the specific person based on the numerical values ​​saved by the analysis means.

[0008] Furthermore, in addition to the configuration described above, the present invention is characterized in that the extraction means and / or the analysis means have a preprocessing means that performs a predetermined preprocessing on the information collected by the extraction means, and the analysis means is a personal characteristic evaluation system that analyzes the information that has undergone the preprocessing.

[0009] Furthermore, in addition to the configuration described above, the present invention is characterized in that the analysis means and / or the evaluation means have a weighting means for weighting the quantified characteristics of the specific person stored by the analysis means in accordance with the reliability of the information, and the evaluation means is a person characteristic evaluation system that evaluates the characteristics of the specific person based on the weighted numerical values.

[0010] Furthermore, in addition to the configuration described above, the present invention is a person characteristic evaluation system that includes a secondary evaluation means in which, after evaluating the specific person, the evaluation means uses the evaluation as a primary evaluation, weights the information collected by the extraction means in accordance with the reliability of the information, and performs a secondary evaluation with the weighting added.

[0011] Furthermore, in addition to the configuration described above, the present invention is characterized in that the analysis means is a personal characteristic evaluation system that analyzes the information to create fields for representing the characteristics of the specific person, and then quantifies the characteristics of the specific person for each field, including the created fields.

[0012] The present invention is also characterized by a person characteristic evaluation device that collects and stores information about a specific person, analyzes the collected and stored information using AI, and generates evaluation information about the specific person.

[0013] The present invention is also characterized by a person characteristic evaluation device having an extraction means for collecting a plurality of pieces of information in which contents relating to a specific person are recorded, an analysis means for analyzing the information collected by the extraction means and quantifying and saving the characteristics of the specific person for each field, and an evaluation means for evaluating the characteristics of the specific person based on the numerical values ​​saved by the analysis means.

[0014] Furthermore, in addition to the configuration described above, the present invention is characterized in that the extraction means and / or the analysis means have a preprocessing means that performs a predetermined preprocessing on the information collected by the extraction means, and the analysis means is a person characteristic evaluation device that analyzes the information that has undergone the preprocessing.

[0015] Furthermore, in addition to the configuration described above, the present invention is characterized in that the analysis means and / or the evaluation means have a weighting means for weighting the quantified characteristics of the specific person stored by the analysis means in accordance with the reliability of the information, and the evaluation means is a person characteristic evaluation device that evaluates the characteristics of the specific person based on the weighted numerical values.

[0016] Furthermore, in addition to the configuration described above, the present invention is a person characteristic evaluation device that includes a secondary evaluation means in which, after evaluating the specific person, the evaluation means uses the evaluation as a primary evaluation, weights the information collected by the extraction means in accordance with the reliability of the information, and performs a secondary evaluation with the weighting added.

[0017] Furthermore, in addition to the configuration described above, the present invention is characterized in that the analysis means is a person characteristic evaluation device that analyzes the information to create fields for representing the characteristics of the specific person, and then quantifies the characteristics of the specific person for each field including the created fields.

[0018] The present invention is also characterized by a method for evaluating personal characteristics, which involves collecting and storing information about a specific person, analyzing the collected and stored information using AI, and generating evaluation information about the specific person.

[0019] The present invention is also characterized by a method for evaluating personal characteristics, comprising an extraction step of collecting a plurality of pieces of information in which details relating to a specific person are recorded, an analysis step of analyzing the information collected in the extraction step and quantifying and saving the characteristics of the specific person for each field, and an evaluation step of evaluating the characteristics of the specific person based on the numerical values ​​saved in the analysis step.

[0020] Furthermore, in addition to the configuration described above, the present invention is characterized in that the extraction step and / or the analysis step include a pre-processing step for performing predetermined pre-processing on the information collected in the extraction step, and the analysis step is configured to analyze the information that has undergone the pre-processing.

[0021] Furthermore, in addition to the configuration described above, the present invention is characterized in that the analysis step and / or the evaluation step include a weighting step of weighting the quantified characteristics of the specific person stored in the analysis step in accordance with the reliability of the information, and the evaluation step evaluates the characteristics of the specific person based on the weighted numerical values.

[0022] Furthermore, in addition to the configuration described above, the present invention is a person characteristic evaluation method characterized in that the evaluation step includes a secondary evaluation step of evaluating the specific person, and then using the evaluation as a primary evaluation, weighting the information collected in the extraction step in accordance with the reliability of the information, and performing a secondary evaluation with the weighting added.

[0023] Furthermore, in addition to the configuration described above, the present invention is characterized in that the analysis step is a personal characteristic evaluation method in which the information is analyzed to create fields for representing the characteristics of the specific person, and the characteristics of the specific person for each field including the created fields are quantified.

[0024] The present invention is also characterized by a program that causes a computer to execute a process of collecting and storing information about a specific person, analyzing the collected and stored information using AI, and generating evaluation information about the specific person.

[0025] The present invention is also characterized by being a program that causes a computer to execute a process including an extraction step of collecting multiple pieces of information that record content related to a specific person, an analysis step of analyzing the information collected in the extraction step and quantifying and saving the characteristics of the specific person for each field, and an evaluation step of evaluating the characteristics of the specific person based on the numerical values ​​saved in the analysis step.

[0026] Furthermore, in addition to the configuration described above, the present invention is characterized in that the extraction step and / or the analysis step includes a preprocessing step for performing a predetermined preprocessing on the information collected in the extraction step, and the analysis step is a program that causes a computer to execute processing that analyzes the information that has undergone the preprocessing.

[0027] Furthermore, in addition to the configuration described above, the present invention is characterized in that the analysis process and / or the evaluation process includes a weighting process for weighting the quantified characteristics of the specific person stored in the analysis process in accordance with the reliability of the information, and the evaluation process is a program that causes a computer to execute processing to evaluate the characteristics of the specific person based on the weighted numerical values.

[0028] Furthermore, in addition to the configuration described above, the present invention is characterized in that the evaluation process is a program that causes a computer to execute processing including a secondary evaluation process in which, after evaluating the specific person, the evaluation is used as a primary evaluation, weighting the information collected in the extraction process according to the reliability of the information, and performing a secondary evaluation with the weighting added.

[0029] In addition to the configuration described above, the present invention is characterized in that the analysis process is a program that causes a computer to execute a process that analyzes the information to create fields for representing the characteristics of the specific person, and then quantifies the characteristics of the specific person for each field, including the created fields. [Effects of the Invention]

[0030] According to the present invention, by collecting information about a specific person and subjecting it to AI analysis, evaluation information for that specific person is generated. This allows information to be collected from everyday work, etc., to evaluate a person's characteristics, and allows for a more accurate evaluation of a person's characteristics in line with actual circumstances. As a result, it becomes possible to hire better personnel and conduct more accurate personnel evaluations. Furthermore, results can be obtained automatically and reliably using AI.

[0031] Furthermore, according to the present invention, multiple pieces of information about a specific person are collected, analyzed, and the characteristics of each field are quantified, and the person's characteristics are evaluated based on these numerical values. Therefore, information can be collected continuously or intermittently from everyday work, etc., and used for evaluating the person's characteristics, and a more realistic evaluation of the person's characteristics can be reliably performed. As a result, it becomes possible to hire better personnel and perform more accurate personnel evaluations.

[0032] Furthermore, according to the present invention, the collected information is subjected to predetermined preprocessing before being analyzed and evaluated, thereby enabling more and more accurate information to be obtained, and enabling a more reliable evaluation of a person's characteristics.

[0033] Furthermore, according to the present invention, collected information is weighted according to the reliability of the information before analysis and evaluation, thereby enabling a more accurate evaluation of a person's characteristics.

[0034] Furthermore, according to the present invention, after a primary evaluation is performed on the collected information, a secondary evaluation is performed by weighting the information according to its reliability, and the results of the secondary evaluation are used for the evaluation, thereby enabling a more accurate evaluation of a person's characteristics.

[0035] Furthermore, according to the present invention, information is analyzed to create fields that represent the characteristics of a specific person, and then the characteristics of each field are quantified, thereby enabling a more accurate evaluation of a person's characteristics, including fields that were not originally considered. [Brief explanation of the drawings]

[0036] [Figure 1] 1 is a functional block diagram showing an outline of a personal characteristic evaluation system according to an embodiment of the present invention; [Figure 2] 3 is a flowchart showing an evaluation flow of the person characteristic evaluation system according to the embodiment. [Figure 3] 10 is a table showing an example of information collection in the person characteristics evaluation system according to the embodiment. [Figure 4] FIG. 2 is a diagram showing an example of a result display screen of the person characteristics evaluation system according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0037] Hereinafter, an embodiment of the present invention will be described.

[0038] 1 to 4 show an embodiment of the present invention.

[0039] The person characteristic evaluation system 1 of this embodiment is a system that collects information about a specific person in the course of daily work, etc., within an obtainable range, such as on a network N, and evaluates the characteristics of the specific person from the information. The obtainable range of information may be, for example, terminals, servers, etc. on an internal company network, accessible servers on the Internet, and interactions on social networking sites. It is preferable to obtain information from as many locations as possible among these, but in some cases, it may be possible to obtain information only from an appropriately limited range (for example, if only internal company evaluations are desired, information is obtained only from within the internal company network, and if only external evaluations are desired, only information on the Internet is obtained).

[0040] Furthermore, the specific person referred to here may be a person limited to an appropriate range, such as an employee of a company or a member of a specified membership organization registered with a job placement agency, or it may be a person of the general public without specifying a range, and an evaluation of the characteristics of each arbitrary person may be performed, as long as it is determined appropriately depending on the purpose, situation, etc.

[0041] Furthermore, as shown in FIG. 1, the person characteristic evaluation system 1 of this embodiment is composed of a server, a terminal, etc. connected to a network N, and in particular has an extraction means 10, an analysis means 20, an evaluation means 30, and a database DB for storing information obtained by these means, numerical values ​​related to evaluation, etc.

[0042] Among these, the extraction means 10 collects multiple pieces of information containing content related to a specific person via a network N, constantly or intermittently monitoring the network N to search for and acquire information related to the specific person. The system includes terminals 2 and 4 and a server 3 connected to the network N, from which appropriate information is acquired. While text information is preferred as the collected information, appropriate information such as image information, video information, and audio information may also be used, or a combination of these may be used. For example, the system may extract information considered to be related to a specific person from email text, attachments, social media exchanges, internal documents on a network such as a server, word of mouth, etc. This information extraction may be performed using AI to select and sort the information. The extraction means 10 simultaneously collects multiple pieces of information related to the specific person depending on the time and situation.

[0043] The analysis means 20 analyzes and quantifies the information collected by the extraction means 10 for evaluation, generating scores for each field (perspective) from the extracted information. For example, the analysis means 20 pre-determines the characteristics of a specific person, such as logic, drive, honesty, politeness, empathy, creativity, curiosity, culture, fairness, insight, foresight, rationality, calmness, strategic thinking, boldness, agility, efficiency, thoroughness, tenacity, flexibility, diligence, leadership, followership, humility, autonomy, energy, affability, passion, toughness, sociability, responsibility, kindness, likability, luck, numerical sense, technical knowledge, legal knowledge, financial knowledge, and intellectual property knowledge. If the information obtained contains descriptions related to these characteristics, the analysis means 20 analyzes whether the information indicates a high or low evaluation of the specific person, converts them into numbers, and stores the results. This analysis may also be performed using AI.

[0044] Furthermore, if the AI ​​determines during its analysis that there is a field other than the pre-set fields (perspectives) that is necessary to express the characteristics of the specific person (that is, that it is a field that is suitable for expressing the characteristics of the specific person), it may create that field and assign a score to that field. The field may be temporarily used only for that specific person, or the field used for that specific person may be registered as the field to be used in the evaluation of all people.

[0045] Furthermore, the analysis means 20 here has a preprocessing means 21, and performs preprocessing before the above-mentioned analysis. This preprocessing may involve converting information other than text into text and analyzing the text information, so-called embedding, adding or removing metadata, removing or adding symbols or the like to standardize information, standardizing character types, etc. These may be performed as appropriate depending on the information, acquisition conditions, etc.

[0046] Furthermore, in this preprocessing, for example, when extracting the evaluation of a specific person from the text of an email, if the email is addressed to multiple people, it is preferable that the AI ​​does not simply evaluate everyone, but rather identifies which of the recipients the evaluation is written for in the text, and then performs processing to generate a score as the evaluation for that person. By performing such processing, when text to be analyzed, evaluated, and scored is obtained using various methods and locations, it can be recognized as being addressed to an appropriate specific person, and an appropriate evaluation can be obtained even if people other than that person are included in the "to" or "cc" fields of the email.

[0047] After that, analysis is performed. In this embodiment, a primary analysis is performed in which each piece of information is analyzed without weighting. Then, a weighting unit 25 is provided to weight the scores obtained after the primary analysis according to the reliability of the information obtained. A secondary analysis is performed in which the information is weighted and then analyzed. Here, weighting according to the reliability of the information is performed according to the reliability of the information source. For example, if there is information that "a particular person has extensive knowledge about patents," the reliability of the information may change depending on whether the source is a patent attorney (high reliability) or a new employee (low reliability). Similarly, similar information may also be weighted because its credibility varies depending on the source. After the weighting described above is performed, the information is quantified. Weighting may be varied depending on the source, the organization to which the information belongs, an external service, etc.

[0048] Furthermore, when assigning this weighting, an evaluation is made of each person's field when analyzing the information source. For example, information from a person with a high insight rating, as shown in the table in Figure 3, may be weighted more highly, while information from a person with a low rating may be weighted less highly. This allows the weighting value (addition rate) to fluctuate, allowing for evaluations that take the current situation into account more effectively, resulting in more accurate evaluation results. Note that the weighting standard may be calculated using an appropriate statistical calculation method, such as the average value or standard deviation. Furthermore, using AI learning functions allows for more accurate weighting standards to be created.

[0049] Weighting may also be done taking into account time, region, location, etc. For example, if the same person has made similar evaluations multiple times in a short period of time, it may be possible to consider the possibility that the person has a tendency to praise others too much, and the second and subsequent evaluations may not be included in the score or may be given a lower score. Also, if there are regional differences in evaluations for the same field, such as between Asia and Europe, or Tokyo and Osaka, weighting may be done taking into account those regional differences.

[0050] The system also includes an evaluation means 30 that evaluates the characteristics of a specific person based on the numerical values ​​stored in the analysis means 20. Here, weighting is performed by the analysis means 20, but weighting may also be performed by the evaluation means 30. In this case, the primary evaluation means 31 evaluates the specific person (primary evaluation) without weighting, and then the secondary evaluation means 32 weights the information collected by the extraction means 10 according to the reliability of the provider, and performs a secondary evaluation with the weighting added. In some cases, after weighting each piece of information by the analysis means 20, the evaluation means 30 may also weight the information overall.

[0051] Further, although the pre-processing is performed in the analysis means 20 here, the pre-processing may be performed in the extraction means 10 before being sent to the analysis means 20.

[0052] Furthermore, existing methods can be used for analysis and evaluation, and appropriate methods such as general-purpose LLM, deep learning models, and cosine similarity of embedding results can be used.

[0053] Furthermore, in this embodiment, these results are configured to be displayed together on the screen, and when the evaluation of a specific person is called up, it is displayed on a summary screen, for example, as shown in FIG.

[0054] Next, the evaluation flow will be explained with reference to FIG.

[0055] First, information is collected by the extraction means 10 (step S1).

[0056] The input data D1 thus obtained is then subjected to comment preprocessing by the preprocessing means 21 of the analysis means 20 (step S2).

[0057] Next, the processed input data D2 that has been preprocessed (converted to text, etc.) by the preprocessing means 21 is subjected to a primary comment analysis from the viewpoints of the evaluation viewpoint database B1 (step S3). Next, the uncorrected score D3 thus obtained is subjected to a secondary analysis of the comments using the evaluation viewpoint database B1 and the evaluation database B2 that takes into account the weighting (step S4).

[0058] Using the corrected score D4 obtained in this way, an evaluation is made in each field (step S5), and the characteristic evaluation for the specific person is displayed (see FIG. 4). The results are fed back to each database B1, B2 (dotted arrows). As mentioned above, a comprehensive weighting may also be applied during the evaluation, and a secondary evaluation may be made on the primary evaluation.

[0059] As described above, according to this embodiment, information about a specific person (e.g., text information, or other information is also acceptable) is collected and subjected to AI analysis to generate evaluation information for that specific person. This allows information to be collected from everyday work, etc., to evaluate a person's characteristics, and more reliably evaluate a person's characteristics in line with the actual situation. As a result, it becomes possible to hire better personnel and perform more accurate personnel evaluations. Furthermore, results can be obtained automatically and reliably using AI.

[0060] Furthermore, according to this embodiment, multiple pieces of information about a specific person are collected, analyzed, and the characteristics of each field are quantified, and the person's characteristics are evaluated based on these numerical values. Therefore, information can be collected continuously or intermittently from everyday work, etc., and used for evaluating the person's characteristics, and a more realistic evaluation of the person's characteristics can be reliably performed. As a result, it becomes possible to hire better personnel and perform more accurate personnel evaluations.

[0061] Furthermore, according to this embodiment, the collected information is subjected to a predetermined preprocessing (for example, collected information that has not been converted into text is preprocessed to convert it into text information, embedding is performed, etc.) before it is analyzed and evaluated, so that more information and more accurate information can be obtained, and a more reliable evaluation of a person's characteristics can be performed.

[0062] Furthermore, according to this embodiment, the collected information is weighted according to the reliability of the information (for example, the reliability of the information source) before analysis and evaluation, thereby enabling a more accurate evaluation of a person's characteristics.

[0063] Furthermore, according to this embodiment, after a primary evaluation is performed on the collected information, a secondary evaluation is performed by weighting the information according to the reliability of the information (for example, the reliability of the source of the information), and the results of the secondary evaluation are used for the evaluation, thereby enabling a more accurate evaluation of a person's characteristics.

[0064] Furthermore, in this embodiment, by analyzing information and creating fields to represent the characteristics of a specific person, and then quantifying the characteristics for each field, it is possible to more accurately evaluate a person's characteristics, including fields that were not originally considered.

[0065] The present invention is not limited to the above-described embodiments, but can also be applied to other configurations and other usage situations.

[0066] For example, in the above-described embodiment, a personal characteristic evaluation system established as a system connected via the Internet has been described, but the present invention is not limited to this and may be established as a standalone device. Furthermore, the present invention may be a program for realizing the contents of the present invention, in which case the program may be applied to an appropriate system or device to realize the invention. Furthermore, the system is not limited to one connected via the Internet and may be one established via other networks (intranet, closed network, etc.). Furthermore, the system may be one connected via wired and / or wireless connections. [Explanation of symbols]

[0067] 1. Personality trait evaluation system 2,4 Devices 3 Server 10 Extraction means 20 Analytical tools 21 Pretreatment means 25 Weighting Method 30 Evaluation tools 31 Primary evaluation tools 32 Secondary evaluation tools N Network

Claims

1. A personal characteristic evaluation system that collects and stores information about a specific person, analyzes the collected and stored information using AI, and generates evaluation information for the specific person.

2. An extraction means for collecting a plurality of pieces of information in which contents relating to a specific person are recorded; an analysis means for analyzing the information collected by the extraction means, quantifying the characteristics of the specific person for each field, and storing the quantified characteristics; evaluation means for evaluating the characteristics of the specific person based on the values ​​stored in the analysis means; A person characteristic evaluation system comprising:

3. the extracting means and / or the analyzing means has a preprocessing means for performing a predetermined preprocessing on the information collected by the extracting means, 3. The system for evaluating personal characteristics according to claim 2, wherein said analyzing means analyzes the information that has undergone the preprocessing.

4. the analysis means and / or the evaluation means includes a weighting means for weighting the quantified characteristics of the specific person stored by the analysis means in accordance with the reliability of the information, 3. The system for evaluating personal characteristics according to claim 2, wherein said evaluation means evaluates the characteristics of said specific person based on the weighted numerical value.

5. The person characteristic evaluation system according to claim 2, characterized in that the evaluation means has a secondary evaluation means that, after evaluating the specific person, uses the evaluation as a primary evaluation, weights the information collected by the extraction means in accordance with the reliability of the information, and performs a secondary evaluation with the weighting added.

6. The person characteristic evaluation system described in claim 2, characterized in that the analysis means analyzes the information to create fields to represent the characteristics of the specific person, and then quantifies the characteristics of the specific person for each field, including the created fields.

7. A person characteristic evaluation device that collects and stores information about a specific person, analyzes the collected and stored information using AI, and generates evaluation information for the specific person.

8. An extraction means for collecting a plurality of pieces of information in which contents relating to a specific person are recorded; an analysis means for analyzing the information collected by the extraction means, quantifying the characteristics of the specific person for each field, and storing the quantified characteristics; evaluation means for evaluating the characteristics of the specific person based on the values ​​stored in the analysis means; A person characteristic evaluation device comprising:

9. the extracting means and / or the analyzing means has a preprocessing means for performing a predetermined preprocessing on the information collected by the extracting means, 9. The person characteristic evaluation device according to claim 8, wherein said analysis means analyzes the information that has undergone the preprocessing.

10. the analysis means and / or the evaluation means includes a weighting means for weighting the quantified characteristics of the specific person stored by the analysis means in accordance with the reliability of the information, 9. The person characteristic evaluation device according to claim 8, wherein said evaluation means evaluates the characteristics of said specific person based on the weighted numerical value.

11. 9. The person characteristics evaluation device according to claim 8, wherein the evaluation means comprises a secondary evaluation means for, after evaluating the specific person, weighting the evaluation as a primary evaluation in accordance with the reliability of the information collected by the extraction means, and performing a secondary evaluation to which the weighting is added.

12. 9. The person characteristic evaluation device according to claim 8, wherein the analysis means analyzes the information to create fields for expressing the characteristics of the specific person, and then quantifies the characteristics of the specific person for each field including the created fields.

13. A method for evaluating personal characteristics, comprising collecting and storing information about a specific person, analyzing the collected and stored information using AI, and generating evaluation information about the specific person.

14. An extraction step of collecting a plurality of pieces of information in which contents relating to a specific person are recorded; an analysis step of analyzing the information collected in the extraction step, quantifying the characteristics of the specific person for each field, and storing the quantified characteristics; an evaluation step of evaluating the characteristics of the specific person based on the values ​​stored in the analysis step; A person characteristic evaluation method comprising:

15. the extraction step and / or the analysis step includes a pre-processing step for performing a predetermined pre-processing on the information collected in the extraction step, 15. The method for evaluating personality characteristics according to claim 14, wherein said analyzing step analyzes the information that has undergone the preprocessing.

16. the analyzing step and / or the evaluating step includes a weighting step of weighting the quantified characteristics of the specific person stored in the analyzing step in accordance with the reliability of the information, 15. The method for evaluating personality characteristics according to claim 14, wherein said evaluation step evaluates the personality characteristics of said specific person based on the weighted numerical values.

17. 15. The person characteristic evaluation method according to claim 14, wherein the evaluation step includes a secondary evaluation step of, after evaluating the specific person, weighting the evaluation as a primary evaluation in accordance with the reliability of the information collected in the extraction step, and performing a secondary evaluation to which the weighting is applied.

18. 15. The method for evaluating personal characteristics according to claim 14, wherein the analysis step involves analyzing the information to create fields for expressing the characteristics of the specific person, and then quantifying the characteristics of the specific person for each field including the created fields.

19. A program that causes a computer to execute a process of collecting and storing information about a specific person, analyzing the collected and stored information using AI, and generating evaluation information about the specific person.

20. An extraction step of collecting a plurality of pieces of information in which contents relating to a specific person are recorded; an analysis step of analyzing the information collected in the extraction step, quantifying the characteristics of the specific person for each field, and storing the quantified characteristics; an evaluation step of evaluating the characteristics of the specific person based on the values ​​stored in the analysis step; A program that causes a computer to execute a process comprising:

21. the extraction step and / or the analysis step includes a pre-processing step for performing a predetermined pre-processing on the information collected in the extraction step, 21. The program according to claim 20, wherein the analyzing step causes a computer to execute a process for analyzing the pre-processed information.

22. the analyzing step and / or the evaluating step includes a weighting step of weighting the quantified characteristics of the specific person stored in the analyzing step in accordance with the reliability of the information, 21. The program according to claim 20, wherein the evaluation step causes a computer to execute a process for evaluating the characteristics of the specific person based on the weighted numerical value.

23. The program according to claim 20, wherein the evaluation step causes a computer to execute processing including a secondary evaluation step of, after evaluating the specific person, using the evaluation as a primary evaluation and weighting the information collected in the extraction step in accordance with the reliability of the information, and performing a secondary evaluation with the weighting added.

24. The program described in claim 20, characterized in that the analysis step causes a computer to execute a process that analyzes the information to create fields to represent the characteristics of the specific person, and then quantifies the characteristics of the specific person for each field, including the created fields.

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