Information processing device and program

Abstract

To provide a technology that utilizes the results of personality tests on other personnel to help them make better use of their personnel. [Solution] An information processing device 1 can perform various types of personality estimation using questionnaire response results, image data obtained by photographing a face, image data obtained by photographing the upper body or the entire body, and genome analysis results as personal information for personality estimation. For the personality of any of the subjects for whom personality estimation has been performed, a distribution specification unit 1C and a position calculation unit 1D calculate the relative position of the subject relative to a group of subjects for which the subject is assumed, such as subjects belonging to an organization or a divisional unit of an organization (e.g., a department). This allows the personality of any subject to be understood as their relative position within the assumed group.

Description

[Technical Field]

[0001] The present invention relates to an information processing device and a program. [Background technology]

[0002] Organizations such as companies need to hire personnel who are useful to the organization and assign them to appropriate departments. The personnel to be hired must be determined taking into consideration not only their abilities but also their personality. For this reason, aptitude tests that can diagnose personality, such as the SPI, are conducted, and information processing devices are used to support organizations in hiring the personnel they need based on the results of the diagnosis, including personality (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2001-297160 Summary of the Invention [Problem to be solved by the invention]

[0004] In reality, the personality traits desired for the personnel to be hired, or for the department to which the personnel will be assigned, are often determined by the image held by the person in charge. In order to make the most of personnel, it is thought that the results of personality diagnoses (personality estimates) from aptitude tests administered to other personnel should be used more effectively. Personality diagnoses are also conducted in ways other than aptitude tests, and the type of personality diagnoses themselves is not particularly limited.

[0005] The present invention aims to provide a technology for supporting the utilization of human resources by utilizing the results of personality tests on other human resources. [Means for solving the problem]

[0006] According to the present invention, an information acquisition unit that acquires, for each of the subjects of diagnosis, personal information that can be used to estimate the personality of the subject of diagnosis, the subjects of diagnosis being at least one of those who belong to an organization and those who wish to work at the organization; The personal information acquired by the information acquisition unit is used to determine the personality of each of the subjects to be diagnosed. The levels shown are estimated using different methods. Estimate Multiple A personality estimation unit; The aforementioned Multiple The personality estimated for each of the diagnostic subjects by the personality estimation unit Level indicating Using the above, for each division unit of the organization assumed in the organization, Multiple The personality of the person being diagnosed Level indicating of frequency a distribution specifying unit that specifies a distribution; The distribution specified for each division unit by the distribution specifying unit frequency Based on the distribution, the personnel subject who is the diagnostic subject of interest among the diagnostic subjects is divided into the division units. The position is personality The relative frequency distribution of the level a position calculation unit that calculates a position; Equipped with 、 Each of the personality estimation units estimates a level indicating the personality of the person to be diagnosed for one or more items predetermined for each personality estimation unit, the distribution specification unit determines one level representing the personality of each of the diagnostic subjects based on the two or more levels representing the personalities estimated by the two or more personality specification units for the items for which the two or more personality specification units have estimated the personality levels of the diagnostic subjects, and specifies the frequency distribution; the position calculation unit calculates, for each of the items, a relative position of a level indicating the personality of the personnel candidate in the frequency distribution. Information processing device And, a recommended personality specification unit that specifies an estimated level for each item indicating the personality of a role model that has achieved high results for each department or each type of work content within the department; The system further includes a recommended assignment specifying unit that specifies an assignment of the person to be diagnosed based on a similarity between a level estimated for each item indicating the personality of a role model for each department or each type of work content within a department and a level estimated for each item indicating the personality of the person to be diagnosed. An information processing device is provided . [Effects of the Invention]

[0007] In the present invention, the results of personality tests on other personnel can be used to support the utilization of personnel more effectively. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a diagram illustrating an information processing device according to an embodiment of the present invention and an overview of a personnel matching service provided by the information processing device. [Figure 2] 2 is a diagram illustrating an example of the hardware configuration of an AP server that is an information processing device according to an embodiment of the present invention. FIG. [Figure 3] FIG. 2 is a diagram illustrating an example of a functional configuration realized on an AP server that is an information processing device according to an embodiment of the present invention. [Figure 4] 10 is a flowchart illustrating an example of a questionnaire-based personality estimation process. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. FIG. 1 is a diagram illustrating an information processing device according to one embodiment of the present invention and an overview of a personnel matching service provided by the information processing device.

[0010] The information processing device 1 is installed to provide a talent matching service to support personnel or managers in organizations such as companies so that they can perform personnel tasks more easily and appropriately. This information processing device 1 is installed, for example, within the company itself or is realized using a cloud service. Hereinafter, organizations that use the talent matching service will be referred to as "target organizations" to distinguish them.

[0011] More specifically, the talent matching service provided is intended to help target organizations more reliably secure suitable talent, or more easily assign people working at the target organizations (hereinafter referred to as "employees") to more appropriate positions. As talent acquisition is also a target of support, users also include people outside the target organizations. These people are primarily those who wish to work at the target organizations (hereinafter referred to as "applicants"). Users within the target organizations are primarily employees, human resources personnel in charge of the personnel affairs of those employees, and managers in a position to manage employees. For convenience, users within the target organizations other than employees will hereinafter be collectively referred to as "managers." The talent matching service provided will hereinafter be referred to as "this service." This service is only available to registered individuals, i.e., only those who log in.

[0012] The tasks in which a person can demonstrate their abilities depend largely on personality. In other words, some tasks are better suited to certain personalities than others, depending on their content. Personality compatibility with employees in a division, which is an organizational division divided according to the tasks and duties they are responsible for, can also be an important factor. For this reason, this service helps enable more appropriate responses to personnel based on personality. As a result, the subjects (hereafter referred to as "subjects") whose personality traits are estimated through personality assessment are primarily employees and applicants. Managers with human resources authority are provided with information that enables them to respond more appropriately to personnel.

[0013] 1 shows a subject terminal 2 used by the person being diagnosed and an administrator terminal 3 used by the administrator as terminals that are information processing devices that communicate directly or indirectly with the information processing device 1. The subject terminal 2 is, for example, a desktop PC (Personal Computer), and is connected to a display 2A, a keyboard 2B, a mouse 2C, and a camera 2D. The administrator terminal 3 also has, for example, a display and a keyboard mounted thereon or connected thereto.

[0014] There are several types of personality assessments, or methods for estimating personality. Currently, the most commonly used method in companies and other organizations is a questionnaire in which participants are presented with a number of questions and asked to select the answer that best applies to them. Examples of this type of personality assessment include the SPI, the Big Five, and the MBTI (Myers-Briggs Type Indicator).

[0015] 1, the information processing device 1 includes, as an example of a functional configuration, a questionnaire implementation unit 1A, a personality estimation unit 1B, a distribution specification unit 1C, and a position calculation unit 1D. The questionnaire implementation unit 1A is configured to administer a questionnaire to subjects for personality diagnosis, i.e., personality estimation, to obtain personal information for personality estimation.

[0016] The survey questions are displayed on the display 2A by the subject terminal 2. The subject answers by selecting one of the options presented in the question. The subject can select one of the options by operating the keyboard 2B or mouse 2C. The answers are managed by the survey implementation unit 1A.

[0017] The personality estimation unit 1B estimates the personality of a subject using personal information. In order to be able to handle various types of personal information, the personality estimation unit 1B is provided with first to fourth personality estimation units 1BA to 1BD that target different types of personal information. The first personality estimation unit 1BA estimates personality using the results of a questionnaire as personal information.

[0018] Currently, there are also other methods such as a face method that estimates personality from the contours of the face, the shapes of features, and their relative positions, a skeleton method that estimates personality from the shape of the skeleton, and a genome method that estimates personality from genomic features. The second to fourth personality estimation units 1BB to 1BD correspond to these methods, respectively.

[0019] In the face method and the skeleton method, image data representing the subject is personal information for personality estimation. Such image data can be acquired by photographing with the camera 2D. Therefore, the second and third personality estimation units 1BB and 1BC perform personality estimation using image data received from the subject terminal 2. Therefore, the image data is personal information for personality estimation.

[0020] The subject can send their own cells, such as hair or blood, as a sample to the genome analysis company 4 and request genome analysis for personality diagnosis. The subject can have the results of the genome analysis conducted in response to the request transmitted to the information processing device 1 by themselves. The analysis results can also be transmitted from the genome analysis company 4 to the information processing device 1. When the information processing device 1 receives the analysis results, the fourth personality estimation unit 1BD can perform personality estimation using the analysis results. Therefore, the genome analysis results are also personal information for personality estimation.

[0021] Only one of the estimation results from the first to fourth personality estimation units 1BA to 1BD may be validated, but two or more estimation results may be integrated to obtain a comprehensive estimation result.

[0022] The first to fourth personality estimation units 1BA to 1BD estimate (evaluate) the personality of the subject for each predetermined item. Some of the items are common to two or more personality estimation units, and some have a relatively high influence on items estimated by other personality estimation units. For example, the third personality estimation unit 1BC of the skeletal system may estimate (evaluate) the subject's personality as follows: · Careful ·Study person Listen carefully and act accordingly · Follow your word There are some inflexible aspects ·Analytical skills Leader type who is good at bringing people together

[0023] The estimation of each of these items or similar items is also performed by the first personality estimation unit 1BA. For this reason, two or more estimation results may be integrated to obtain a comprehensive estimation result. The method for obtaining the comprehensive estimation result is not particularly limited. For example, a base method may be determined, and the estimation result for each item obtained by the base method may be manipulated depending on whether the estimation result for each item obtained by the base method matches the directionality of the same item or related items obtained by another method. For example, the reliability of the estimation result for the item obtained by the base method may be evaluated based on the estimation result for the item obtained by another method, and the estimation result for the item obtained by the base method may be manipulated depending on the evaluation result.

[0024] This service assumes that all employees belonging to a target organization will be subjected to personality estimation as subjects. Based on this assumption, this service identifies the distribution of the personalities of each subject belonging to the entire target organization or for each division unit of the target organization, and calculates and identifies the personality position of any one of the subjects (a personnel subject) on that distribution. The distribution identification unit 1C identifies the distribution, and the position calculation unit 1D calculates the personality position of that person. In the following, we will assume that the division unit is a "department."

[0025] The administrator can check the calculation results of this personality position at will. The example output shown in Figure 1 allows the subject to check the estimated results for each item in a table arranged alongside the Japan average and the test average. The test average is the average for the entire subject organization, or for all subjects in a single department. In a subject organization with multiple departments, it is often the average for a single department. For this reason, the test average refers to the average for a single department unless otherwise specified. Such calculation results may be made available for viewing by the subject.

[0026] In the example output result shown in FIG. 1, the estimation results for each item of the subject are expressed as a numerical value between 0 and 100, for example. In the estimation results for each item of the subject, two different shadings are used: item A and item C. This shading is performed based on the calculation results of the position for each item. The shading for the estimation result of item A is performed, for example, when it is in the top 5%. The shading for the estimation result of item C is performed, for example, when it is in the bottom 20%. In this embodiment, the presence or absence of shading and the type of shading make it possible to visually recognize the position of the estimation result for each item.

[0027] From these output results, managers can check the personality ranking of the personnel candidate in any department for each item. By utilizing the results of personality estimation (personality diagnosis) of other candidates, the personality of the personnel candidate can be evaluated relatively.

[0028] For example, in a department with high performance, unless the high performance is due to an individual, it can be assumed that there are many candidates with personalities suited to the work of that department. Therefore, it can be assumed that it is desirable to assign personnel candidates with personalities similar to the many candidates to that department. On the other hand, in a department with low performance, unless the low performance is due to an individual, it can be assumed that there are few or no candidates with personalities suited to the work of that department. Therefore, it can be assumed that it is desirable to assign personnel candidates with personalities different from the many candidates to that department.

[0029] As a result, managers can more appropriately and easily identify candidates who are suitable for departments that are short-staffed or have low performance. For employees, it is easier to identify departments that are more suitable for them. As a result, presenting the personality estimation results of personnel candidates in relation to the personality estimation results (personality assessment) of other subjects is effective in supporting the utilization of human resources. This result also has the effect of improving work efficiency for managers.

[0030] Hereinafter, the embodiments of the present invention will be described in detail with further reference to the drawings. 2 is a diagram showing an example of the hardware configuration of an AP server, which is an information processing device according to one embodiment of the present invention. This hardware configuration is merely an example and is not particularly limited. For example, although only one CPU (Central Processing Unit) 21 and one GPU (Graphics Processing Unit) 24 are shown, multiple units of each may be installed.

[0031] The information processing device 1 is realized as an AP server that is installed, for example, by the target organization in a management facility or using a cloud service to provide the service. For this reason, the AP server is designated by the reference numeral "1." For this reason, hereinafter, the "information processing device" will also be referred to as the "AP server." Communication can be performed via a network 30 between a target terminal 2 used by a target person (e.g., an employee) and an administrator terminal 3. The network 30 is, for example, a LAN (Local Area Network) or a composite network including the Internet.

[0032] 2, the AP server 1 has a configuration in which a CPU 21, a ROM (Read Only Memory) 22, a RAM (Random Access Memory) 23, a GPU 24, a NIC (Network Interface Card) 25, an auxiliary storage device 26, a media drive 27, and an I / FC (Interface Controller) group 28 are connected to a bus 29. A VRAM (Video RAM) 24A is connected to the GPU 24.

[0033] The auxiliary storage device 26 is a device capable of permanently storing data, such as a hard disk drive or a solid state drive (SSD). The media drive 27 is a device into which the media 27A, which is a recording medium, can be detachably attached. The media 27A is, for example, a compact disc (CD)-ROM, a DVD-ROM, a DVD-RAM, etc.

[0034] The I / FC group 28 includes various I / FCs that enable communication with various peripheral devices or external devices, including an input device 28A and a display device 28B. The input device 28A and the display device 28B are temporarily connected to the I / FC group 28 as needed. The auxiliary storage device 26 stores, as programs, an operating system (OS) and various application programs that run on the OS. One of the various application programs is an application program that enables the provision of this service. Hereinafter, this application will be referred to as the "matching service app."

[0035] The ROM 22 is also a device capable of permanently storing data, and stores, for example, firmware and various data. The CPU 21 reads the firmware stored in the ROM 22 into the RAM 23 and executes it. The firmware then reads the OS stored in the auxiliary storage device 26 into the RAM 23 and executes it. Various application programs, including some matching service apps, are read into the RAM 23 and executed by the OS. The GPU 24 can execute various application programs, including some matching service apps, stored in the auxiliary storage device 26 and read into the VRAM 24A.

[0036] The matching service app may be stored in media 27A and distributed. If network 30 is a composite network, it may be distributed via network 30. When distributed via network 30, the matching service app may be stored in a recording medium that can be directly or indirectly accessed by the information processing device that distributes it. In other words, the storage medium may be one that can be directly or indirectly accessed by another information processing device that can communicate with the information processing device that distributes it.

[0037] 3 is a diagram showing an example of a functional configuration realized on an AP server, which is an information processing device according to one embodiment of the present invention. This functional configuration example is mainly realized by the CPU 21 and the GPU 24 respectively executing different parts of the above-mentioned matching service application. Note that the functional configuration is not particularly limited, and various modifications are possible.

[0038] As shown in Figure 3, the CPU 21 of the AP server 1 has the following functional configuration: a transmission / reception processing unit 211, a screen generation unit 212, a questionnaire implementation unit 213, a facial feature extraction unit 214, a skeletal feature extraction unit 215, a genome feature extraction unit 216, a comprehensive estimation unit 217, a target result extraction unit 218, a position calculation unit 219, a department-specific tendency identification unit 220, a recommended personality identification unit 221, and a recommended assignment identification unit 222.

[0039] On the GPU 24, a first personality estimation unit 241, a second personality estimation unit 242, a third personality estimation unit 243, and a fourth personality estimation unit 244 are realized as functional components. All of these units use AI (Artificial Intelligence). While this functional configuration is realized on the CPU 21 and the GPU 24, on the auxiliary storage device 26, an estimation result memory unit 261, a department-specific trend information memory unit 262, a recommended personality information memory unit 263, and a performance information memory unit 264 are secured as data storage areas.

[0040] The estimation result storage unit 261 is a storage area reserved for storing estimation result information that indicates the results of personality estimation for each subject. The estimation result information is information including, for example, the subject's name, an ID (ID) that can uniquely identify the subject, a department ID, a type of work content within the department, the date and time of estimation, a type of method, and an estimation result for each item. The ID here is, for example, identification information assigned to each subject by this service for the purpose of providing the service, that is, for logging in. Even within the same department, the work that a subject is engaged in may be divided into different categories. For example, in a sales department, the work is usually subdivided into work such as actual sales work and sales administration work. For this reason, in addition to a department ID that can uniquely identify a department, the estimation result information also includes the type of work within the department. The method type is information that indicates one of, for example, a questionnaire method, a face method, a skeletal method, a genome method, and a comprehensive method.

[0041] The department-specific tendency information storage unit 262 is a storage area reserved for storing department-specific tendency information that indicates the personality tendencies of subjects assigned to each department. The department-specific tendency information is information that includes, for example, the department ID, the type of work, the type of work content within the department, the specified date and time, and the specified result of each item.

[0042] The identification result for each item is, for example, an estimated average or median. Even within the same department, the work content in which the subject is engaged may be divided as described above. For this reason, in this embodiment, department-specific trend information is generated and saved for each department and each work content.

[0043] The recommended personality information storage unit 263 is a storage area reserved for storing recommended personality information that indicates the personality recommended for engaging in the assumed work content, for example, for each department or each work content (work content type within a department). The recommended personality information is generated, for example, by extracting subjects (role models) who have achieved high results from among subjects engaged in the assumed work content. As a result, the recommended personality information is information including, for example, the ID of the subject who will be the role model, the department ID, the work content type within the department, and the estimation results for each item for that subject. The estimation results for each item are extracted from the estimation result information for that subject.

[0044] The achievement information storage unit 264 is a storage area reserved for storing achievement information indicating the achievements achieved by each subject in the work content in which the subject is engaged. The achievement information is information including, for example, the subject's ID, department ID, work content type within the department, and achievement-specific information. The achievement-specific information is information including, for example, the content of the achievement achieved by the subject, the department ID of the department to which the subject was assigned when the achievement was achieved, the work content type within the department, the date the achievement was achieved, and an evaluation. Whether the subject has achieved excellent results can be confirmed by evaluation for each achievement.

[0045] The various data stored in each of the storage units 261 to 264 is actually read into the RAM 23 or the VRAM 24A and processed there. Furthermore, data transfer between the CPU 21 and the GPU 24 is actually performed via the RAM 23. Communication with the target terminal 2 and the administrator terminal 3 is performed via the NIC 25. For convenience, these are ignored in FIG. 3. This also applies to the following explanation.

[0046] Each of the units 241 to 244 implemented on the GPU 24 has the following functions. The first personality estimation unit 241 estimates the personality of the subject from the results of the questionnaire. The second personality estimation unit 242 estimates the personality of the subject using features extracted from the face represented by the image data. The third personality estimation unit 243 estimates the personality of the subject using feature amounts extracted from the upper body or the entire body of the subject represented by the image data. The fourth personality estimation unit 244 estimates the personality of the subject using the feature amount extracted from the genome analysis result. These personality estimation techniques are well known, and therefore will not be described in detail.

[0047] Each of the units 221 to 227 implemented on the CPU 21 has the following functions. The transmission / reception processing unit 211 performs processing for transmitting and receiving various data including requests between the subject terminal 2, the administrator terminal 3, and the genome analysis company 4 (terminals thereof). The screen generation unit 212 generates screens to be transmitted to the subject terminal 2, the administrator terminal 3, and the genome analysis company 4 (terminals thereof). The transmission / reception processing unit 211 transmits the screens generated by the screen generation unit 212 to the subject terminal 2, the administrator terminal 3, and the genome analysis company 4 (terminals thereof), thereby enabling the transmission of various requests and the display of responses, etc. The output result example shown in FIG. 1 is arranged on a screen generated by the screen generation unit 212.

[0048] The survey implementation unit 213 is used to conduct a survey of the subject using the screen generation unit 212. The survey implementation unit 213 manages the subject's responses to each question. After the survey is completed, the survey implementation unit 213 instructs the first personality estimation unit 241 to estimate a personality using, for example, the response results. This causes the first personality estimation unit 241 to function and acquire a personality estimation result based on the questionnaire. This estimation result is stored in the estimation result storage unit 261 secured in the auxiliary storage device 26.

[0049] The facial feature extraction unit 214 functions when, for example, the subject who transmitted the image data requests face-based personality estimation. The facial feature extraction unit 214 extracts features from the face represented by the transmitted image data and instructs the second personality estimation unit 242 to perform personality estimation using the extracted features. This causes the second personality estimation unit 242 to function and obtain a face-based personality estimation result.

[0050] The skeletal feature extraction unit 215 functions when, for example, the subject who transmitted the image data requests a skeletal-based personality estimation. The skeletal feature extraction unit 215 extracts features from the upper body or the entire body of the subject represented by the image data, and instructs the third personality estimation unit 243 to estimate a personality using the extracted features. This causes the third personality estimation unit 243 to function, and a skeletal-based personality estimation result is obtained.

[0051] The genome feature extraction unit 216 functions, for example, when the subject who has caused the genome analysis results to be transmitted instructs (requests) genome-based personality estimation, or when the genome analysis results are received from the genome analysis company 4. The genome feature extraction unit 216 extracts features from the genome analysis results and instructs the fourth personality estimation unit 244 to estimate personality using the extracted features. This causes the fourth personality estimation unit 244 to function, and the genome-based personality estimation result is obtained.

[0052] As described above, in this embodiment, personality estimation can be performed using multiple methods. Therefore, when a certain method of personality estimation is instructed, there is a possibility that the results of personality estimation using another method already exist. The comprehensive estimation unit 217 is provided to deal with this possibility. Therefore, the comprehensive estimation unit 217 functions after the results of personality estimation using the instructed method have been obtained.

[0053] The comprehensive estimation unit 217 searches using the ID of the subject for whom a personality estimation result has been obtained, and extracts estimation result information having the same ID from the estimation result information stored in the estimation result storage unit 261. After performing the extraction, the comprehensive estimation unit 217 further extracts valid information from the extracted estimation result information. In this way, when there are multiple pieces of estimation result information obtained using the same method, only one of them, for example, the most recent one with the latest date and time, is extracted.

[0054] If only one piece of estimation result information is finally extracted, the comprehensive estimation unit 217 does not generate new estimation result information. However, if there are multiple pieces of estimation result information, the comprehensive estimation unit 217 may determine a base method as described above, evaluate the estimation results for each item obtained using that method using estimation results for items obtained using a different method, and perform operations according to the evaluation results. The estimation results for each item after performing such operations as necessary are newly stored in the estimation result storage unit 261 as estimation result information whose method type indicates comprehensive.

[0055] The target result extraction unit 218 extracts necessary inference result information from the inference result storage unit 261. For example, this extraction is performed by specifying conditions that include at least a department ID and a type of work content within the department. This condition is intended for a case in which a manager considers where to assign a target person.

[0056] The position calculation unit 219 assumes the subject of each piece of estimation result information extracted by the subject result extraction unit 218, and calculates the position of the personality of the personnel candidate for each assumed subject for each item. The position is expressed as a positional relationship among all subjects (for example, within the top five, etc.), a deviation value, etc. By calculating such a position, it is possible to perform shading in the example output result shown in FIG. 1.

[0057] The department-specific trend identification unit 220 identifies personality trends of the target individuals by department and by type of work content within the department, generates department-specific trend information using the identification results, and stores the generated department-specific trend information in the department-specific trend information storage unit 262. The identified personality trends are, for example, the average of each item, or values ​​of each item that are desirable for working in the job, etc. The desirable values ​​of each item can be estimated by regression analysis, etc.

[0058] Such departmental trend information is useful for managers to identify desirable departments for personnel candidates. This is because it is believed that it will be easier and more appropriate to assign personnel candidates with personalities that are thought to match the overall personality tendencies of the personnel in each department. This will make it easier and more appropriate to assign personnel candidates who have become mentally fragile to departments that are suitable for them, for example.

[0059] The recommended personality identification unit 221 identifies, for example, for each department and each type of work content within the department, subjects who have achieved excellent results among subjects engaged in the work specified therein, and generates the recommended personality information using the identified subjects as role models. This recommended personality information is generated using estimated result information of the identified subjects. The generated recommended personality information is stored in the recommended personality information storage unit 263. Whether or not the subject has achieved excellent results is confirmed by referring to the achievement information stored in the achievement information storage unit 264.

[0060] The recommended assignment destination identification unit 222 identifies an assignment destination that is considered appropriate for the personnel candidate designated by the manager. The assignment destination may be identified, for example, by calculating the similarity between the estimated results of each item represented by the estimated personality information stored in the recommended personality information storage unit 263 and the estimated results of each item of the personnel candidate. The similarity may be, for example, the difference between them, or the similarity obtained by regarding the estimated results of each item as a vector. When recommending an assignment destination where there is a candidate with such high similarity, a candidate who is suitable as a role model for the personnel candidate can also be recommended to the personnel candidate.

[0061] FIG. 4 is a flowchart showing an example of a questionnaire-based personality estimation process. This process is executed when, for example, a subject operating subject terminal 2 requests personality estimation by questionnaire. This process itself is realized by executing the matching service app. Next, this process will be described in detail with reference to FIG. 4.

[0062] As described above, part of the matching service application is executed by the GPU 24, and the rest is executed by the CPU 21. The flowchart shown in Fig. 4 is based on the assumption that the processing is executed by the CPU 21. Therefore, the processing is executed by the CPU 21.

[0063] First, in step S11, the CPU 21 conducts a survey in which questions and answer options are sequentially presented to the subject. After the survey is completed, in step S12, the CPU 21 issues a command to estimate personality using the answers to each question. This command activates the first personality estimation unit 241, and the result of personality estimation by the questionnaire method is obtained.

[0064] In the next step S13, CPU 21 determines whether there are any other personality estimation results for the subject who answered the questionnaire. If the subject has had personality estimation performed using another method, estimation result information obtained using that other method exists in estimation result storage unit 261. Therefore, the determination in step S13 is YES, and the process proceeds to step S14. If not, the determination in step S13 is NO, and the process proceeds to step S15.

[0065] In step S14, the CPU 21 generates and saves new inference result information by integrating existing inference result information. In the following step S15, the CPU 21 determines whether the subject is assigned to an organization, i.e., whether the subject is an employee. If the subject is an employee, the determination in step S15 is YES, and the process proceeds to step S16. If the subject is an applicant, the determination in step S15 is NO, and the process proceeds to step S19.

[0066] If the subject is an employee, the subject will be assigned to a department. As a result, the results of the personality estimation may change the contents of at least one of the department-specific tendency information generated for that department and the estimated personality information. For this reason, steps S16 to S18 are performed to deal with such a possibility.

[0067] First, in step S16, CPU 21 extracts, as a target result, estimation result information specified by the department to which the subject belongs and the work content (work content type within the department) in which the subject is engaged, from estimation result storage unit 261. In the following step S17, CPU 21 uses the extracted estimation result information to generate new department-specific tendency information and stores the generated department-specific tendency information in department-specific tendency information storage unit 162. In the subsequent step S18, CPU 21 identifies subjects who have achieved excellent results among subjects who are engaged in the same work content in the department to which the subject belongs, and generates recommended personality information. The generated recommended personality information is stored in recommended personality information storage unit 263. Note that there is a possibility that recommended personality information will not be generated.

[0068] In this way, in this embodiment, information that may be different from the information in the personality estimation is updated as needed, so that the department-specific tendency information and recommended personality information are always kept up to date.

[0069] In step S19 following step S18, the CPU 21 calculates the position of the subject within the personality distribution represented by each piece of estimation result information extracted in step S16. After calculating the position, the questionnaire-based personality estimation process ends. Even when a personality estimation method other than a questionnaire method is requested, the same processing as the questionnaire method personality estimation processing is executed. Therefore, regardless of the method of personality estimation, the department-specific tendency information and recommended personality information are always kept up to date.

[0070] In this embodiment, the position of a personnel target is indicated by the ranking in each item representing the assumed personality space, or by an index (standard deviation) representing that ranking, but the method of expressing the position is not particularly limited. Furthermore, the above examples of how to use the results of personality estimation for other personnel (targets) are merely examples, and various modifications are possible. The method used for personality estimation is also not particularly limited. When multiple methods are used, there is no particular limit to how the results of personality estimation from each method are handled. The group of targets for which the position of a personnel target is calculated is not limited to an organization or a division unit of that organization. A virtual group of targets may be assumed and the position of the personnel target may be calculated.

[0071] In addition, in this embodiment, both applicants who wish to work in the target organization and employees who work in the target organization are considered as the target persons, but only one of them may be considered as the target. Furthermore, the target organization may be multiple, not just one. The divisional units, such as departments, may also be groups of divisional units in which the work content is the same or nearly the same within multiple target organizations. In this way, when multiple target organizations are assumed, it becomes possible to grasp the relative personality position of the personnel target person across the multiple target organizations. [Explanation of symbols]

[0072] 1 Information processing device (AP server), 1A Questionnaire implementation unit, 1B Personality estimation unit, 1BA First personality estimation unit, 1BB Second personality estimation unit, 1BC Third personality estimation unit, 1BD Fourth personality estimation unit, 1C Distribution identification unit, 1D Position calculation unit, 2 Subject terminal, 3 Administrator terminal, 4 Genome analysis company

Claims

1. an information acquisition unit that acquires, for each of the subjects of diagnosis, personal information that can be used to estimate the personality of the subject of diagnosis, the subjects of diagnosis being at least one of those who belong to an organization and those who wish to work at the organization; a plurality of personality estimation units that estimate, for each of the diagnostic subjects, a level indicating the personality of the diagnostic subject by a different estimation method from each other, using the personal information acquired by the information acquisition unit; a distribution specification unit that specifies, for each division unit of the organization assumed in the organization, a frequency distribution of levels indicating the personalities of the plurality of diagnostic subjects belonging to the division unit, using the levels indicating the personalities estimated for each of the diagnostic subjects by the plurality of personality estimation units; a position calculation unit that calculates a position in the division unit of a personnel subject who is a focus of attention among the diagnosis subjects, based on the frequency distribution identified for each division unit by the distribution identification unit, and that calculates a relative position in the frequency distribution of a level indicating personality; Equipped with each of the personality estimation units estimates a level indicating the personality of the person to be diagnosed for one or more items predetermined for each of the personality estimation units; the distribution specification unit determines, for each item for which two or more of the personality estimation units have estimated the personality level of the diagnostic subject, one level representing the personality of each diagnostic subject based on two or more levels representing the personalities estimated by the two or more personality estimation units, and specifies the frequency distribution; the position calculation unit calculates, for each of the items, a relative position of a level indicating the personality of the personnel candidate in the frequency distribution. An information processing device, a recommended personality specification unit that specifies an estimated level for each item indicating the personality of a role model that has achieved high results for each department or each type of work content within the department; The system further includes a recommended assignment specifying unit that specifies an assignment of the person to be diagnosed based on a similarity between a level estimated for each item indicating the personality of a role model for each department or each type of work content within a department and a level estimated for each item indicating the personality of the person to be diagnosed. Information processing device.

2. The mutually different estimation methods include a questionnaire-based method and at least one of a face method, a skeletal method, and a genome method; the distribution specification unit, for items in which the personality level of the diagnostic subject is estimated by at least one of the questionnaire-based method, face method, skeletal method, and genome method, determines one level indicating personality for each diagnostic subject based on two or more levels indicating personality estimated by those methods, and then specifies the frequency distribution; The information processing device according to claim 1 .

3. The division unit for which the position is calculated is one of the division unit to which the personnel target belongs and the division unit that is a candidate for the assignment of the personnel target. The information processing device according to claim 1 .

4. A program for causing a computer to function as an information processing device described in any one of claims 1 to 3.

5. An information acquisition step in which a computer acquires, for each person to be diagnosed, at least one of a person who belongs to an organization and a person who wishes to work at said organization, personal information that enables an estimation of the personality of said person to be diagnosed; a plurality of personality estimation steps in which a computer estimates a level indicating the personality of each of the diagnostic subjects by different estimation methods using the personal information acquired by the information acquisition step; a distribution specification step in which a computer specifies, for each division unit of the organization assumed in the organization, a frequency distribution of levels indicating the personalities of the plurality of diagnostic subjects belonging to the division unit, using the levels indicating the personalities estimated for each of the diagnostic subjects by the plurality of personality specification steps; a position calculation step in which the computer calculates a position in the division unit of the personnel subject who is the subject of diagnosis and who has been focused on among the subjects of diagnosis, based on the frequency distribution specified for each division unit by the distribution specification step, the position being a relative position in the frequency distribution of the level indicating the personality; Equipped with a computer, in each of the personality estimation steps, estimating a level indicating the personality of the person to be diagnosed for one or more items predetermined for each personality estimation step; In the distribution specification step, the computer determines, for each item for which the personality level of the diagnostic subject has been estimated in two or more of the personality estimation steps, one level indicating the personality of each diagnostic subject based on two or more levels indicating the personalities estimated in the two or more personality estimation steps, and then specifies the frequency distribution; an information processing method, wherein in the position calculation step, a computer calculates a relative position of a level indicating the personality of the personnel candidate in the frequency distribution for each of the items, a recommended personality specification step in which the computer specifies an estimated level for each item indicating the personality of a role model that has achieved high results for each department or each type of work content within the department; The method further comprises a step of specifying a recommended assignment for the person to be diagnosed based on the similarity between the level estimated for each item indicating the personality of a role model for each department or each type of work content within a department and the level estimated for each item indicating the personality of the person to be diagnosed. Information processing methods.

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