Information processing device, information processing method, and program

Abstract

Provided are an information processing device, an information processing method, and a program which suitably connect an individual user and human resources sought by a company user. This information processing device comprises a skill information acquisition unit and a potential skill estimation unit. The skill information acquisition unit acquires skill information pertaining to a skill of an individual user. The potential skill estimation unit estimates, from the acquired skill information, potential skill information pertaining to a potential skill of the individual user by using a learning model that has been trained by taking, as teaching data for estimating the potential skill, skill information for training pertaining to the skill of the individual user.

Description

Information processing device, information processing method, and program

[0001] The present disclosure relates to an information processing device, an information processing method, and a program.

[0002] There are matching services that connect companies seeking new employees with individuals seeking companies to hire them, and technologies are being developed to connect such corporate users with individual users.

[0003] For example, a technology has been disclosed that calculates a mind value, which is an index that evaluates an individual's attitude toward an event, from information about the subject entered from the subject's terminal, and calculates a character value, which is an index that evaluates the temperament that has been formed and fixed in the individual, thereby evaluating the individual's potential abilities.

[0004] Japanese Patent Application Laid-Open No. 2003-030316

[0005] Services that connect corporate users and individual users are required to introduce as many people as possible who match the needs of each party. However, individual users do not always register all of their skills in job information. As a result, even if there is a potential match between the needs of both parties, there are cases where an introduction does not occur.

[0006] In view of the above-mentioned problems, the present disclosure aims to provide an information processing device, an information processing method, and a program that suitably connect the human resources desired by corporate users with individual users.

[0007] The information processing device disclosed herein includes a skill information acquisition unit that acquires skill information related to the skills of an individual user, and a latent skill estimation unit that estimates latent skill information related to the latent skills of the individual user from the acquired skill information using a trained learning model that has been trained using the skill information related to the skills of the individual user for learning as teacher data for estimating latent skills.

[0008] The information processing method disclosed herein involves a computer acquiring skill information regarding the skills of an individual user, and estimating latent skill information regarding the individual user's latent skills from the acquired skill information using a trained learning model that has been trained to use the skill information regarding the individual user's skills for learning as training data for estimating latent skills.

[0009] The program disclosed herein acquires skill information regarding the skills of an individual user, and causes a computer to execute a process of estimating latent skill information regarding the individual user's latent skills from the acquired skill information using a trained learning model that has been trained to use the skill information regarding the individual user's skills for learning as training data for estimating latent skills.

[0010] The present disclosure makes it possible to provide an information processing device, an information processing method, and a program that suitably connects personnel desired by corporate users with individual users.

[0011] FIG. 1 is a block diagram showing the configuration of an information processing device according to the present embodiment. FIG. 1 is a block diagram showing the configuration of an information processing device according to the present embodiment. FIG. 2 is a diagram showing the processing of a latent skill estimation unit of the information processing device according to the present embodiment. FIG. 3 is a flowchart showing a notification operation of the information processing device according to the present embodiment. FIG. 4 is a flowchart showing a latent skill correction operation of the information processing device according to the present embodiment. FIG. 4 is a block diagram showing the configuration of an information processing device according to the present embodiment. FIG. 5 is a flowchart showing an example of a notification operation of the information processing device according to the present embodiment. FIG. 6 is a block diagram showing the configuration of a computer according to the present embodiment.

[0012] Hereinafter, specific embodiments to which the present disclosure is applied will be described in detail with reference to the drawings. In each drawing, the same elements are designated by the same reference numerals, and for clarity of explanation, duplicate explanations will be omitted as necessary.

[0013] First Embodiment First, the configuration of an information processing device 100 according to a first embodiment will be described with reference to FIG. 1 . FIG. 1 is a block diagram illustrating an example of the configuration of the information processing device 100 according to this embodiment. The information processing device 100 includes a skill information acquisition unit 101 and a latent skill estimation unit 102. The skill information acquisition unit 101 acquires skill information related to the skills of an individual user. The latent skill estimation unit 102 estimates latent skill information related to the latent skills of the individual user from the acquired skill information related to the skills of the individual user for training, using a trained learning model trained using latent skills related to the latent skills of the training user as training data. Therefore, the information processing device 100 according to the first embodiment can estimate the latent skills of an individual user. As a result, this embodiment can provide an information processing device or the like that effectively connects the talent desired by corporate users with individual users.

[0014] Second Embodiment Next, the configuration of an information processing device 10 according to a second embodiment will be described with reference to FIG. 2 . FIG. 2 is a block diagram illustrating an example of the configuration of the information processing device 10 according to this embodiment. The information processing device 10 is a specific implementation of the information processing device 100 according to the first embodiment. The information processing device 10 is, for example, a computer or a server. The information processing device 10 may be configured to be built on the cloud. The information processing device 10 is used in a matching service that connects corporate users seeking new external personnel for employment with individual users seeking companies to employ them. The information processing device 10 communicates with at least one personal user terminal 20 and at least one corporate user terminal 30 via a network N such as the Internet, and transmits and receives data. The personal user terminal 20 is a terminal such as a smartphone, tablet, or PC (Personal Computer) used by an individual user. The corporate user terminal 30 is a terminal such as a smartphone, tablet, or PC used by a corporate user.

[0015] The information processing device 10 mainly comprises a skill information acquisition unit 11, a latent skill estimation unit 12, a compatibility calculation unit 13, a notification unit 14, a correction acceptance unit 15, and a memory unit 16. The skill information acquisition unit 11 and the latent skill estimation unit 12 correspond to the skill information acquisition unit 101 and the latent skill estimation unit 102 of the information processing device 100, respectively.

[0016] The skill information acquisition unit 11 acquires skill information of an individual user. The skill information acquisition unit 11 acquires the skill information from the individual user terminal 20 or the storage unit 16. The skill information includes at least one skill (skill #1, skill #2, skill #3, ... skill #N) that the individual user actually possesses.

[0017] Skills are, for example, the abilities required for an individual user to perform a specific job. More specifically, skills include the ability to operate a specific machine, the ability to communicate using a specific language, the ability to perform specific skills or actions, etc. Skills may also include the knowledge and work history information possessed by the individual user. Work history information is information indicating the work experience of the individual user, and may include the industry, job type, and period of experience. By including work history information in the skill information, the information processing device 10 can, for example, use the work history to perform weighting when calculating the compatibility. This allows the information processing device 10 to more effectively connect corporate users and individual users. The skill information acquisition unit 11 may acquire skill information from the storage unit 16.

[0018] The latent skill estimation unit 12 uses the trained model M stored in the memory unit 16 to estimate latent skill information, which is skills that an individual user potentially possesses, from the skill information received from the individual user terminal 20. More specifically, the latent skill estimation unit 12 inputs the received skill information of the individual user into the trained model M, and receives the latent skill information as an output in response to this input.

[0019] The latent skill information is at least one latent skill (latent skill #1, latent skill #2, latent skill #3, ... latent skill #N) that the individual user potentially possesses. The latent skill is a skill that is highly related to the individual user's skill information. Specifically, for example, if skill information is received indicating that architectural CAD is usable, the latent skill may be the use of structural calculation software that is highly related to architectural CAD. The trained model M includes the reliability of the estimated latent skill in the latent skill information for such skill information. The reliability of the latent skill is an index indicating the likelihood that the individual user actually possesses the estimated latent skill. The latent skill estimation unit 12 may also determine the skill information primarily used when estimating the latent skill information. The latent skill estimation unit 12 stores the latent skill information and the skill information primarily used when estimating the latent skill information in the storage unit 16.

[0020] 3 is a diagram specifically illustrating an example of the function of the latent skill estimation unit 12 of the information processing device 10 according to this embodiment. As shown in FIG. 3, the latent skill estimation unit 12 inputs skill information (skill #1, skill #2, skill #3, ...) into a trained model M, and estimates latent skill information (latest skill #1 is 60%, latent skill #2 is 15%, latent skill #3 is 5%, ...).

[0021] More specifically, for example, the latent skill estimation unit 12 inputs, as skill information, the ability to use architectural CAD, the ability to use document creation software, a role such as leader or sub-leader, and years of experience into the trained model M. Using the trained model M, the latent skill estimation unit 12 estimates, as latent skill information, a 60% chance of being able to use semiconductor CAD, a 15% chance of being able to use AutoCAD, and a 5% chance of being able to use civil engineering CAD. Furthermore, the latent skill estimation unit 12 determines which skill information skill was primarily used when estimating the latent skill information. In the above example, the latent skill estimation unit 12 determines that architectural CAD skills were primarily used when estimating latent skills such as semiconductor CAD, AutoCAD, and civil engineering CAD.

[0022] The compatibility calculation unit 13 calculates the compatibility between the individual user and the corporate user by comparing at least one of the skill information and the potential skill information with required skill information, which is the skill that the corporate user requires of the individual user. For example, the compatibility is a numerical representation of how much at least one of the skill information and the potential skill information satisfies the required skill information required by the corporate user. The compatibility calculation unit 13 can set the compatibility depending on the possibility of the potential skill included in the potential skill information. The compatibility calculation unit 13 stores the compatibility in the memory unit 16.

[0023] The notification unit 14 notifies at least one of the personal user terminal 20 used by the personal user and the corporate user terminal 30 used by the corporate user of the matching result based on the degree of matching. Specifically, if the degree of matching is equal to or greater than a predetermined threshold, the notification unit 14 notifies at least one of the personal user terminal 20 and the corporate user terminal 30 of the skill information, latent skill information, required skill information, and degree of matching. In addition, the notification unit 14 notifies the personal user terminal 20 of the skill information that was mainly used when estimating the latent skill information determined by the latent skill estimation unit 12.

[0024] The correction receiving unit 15 presents the latent skill information stored in the storage unit 16 to the individual user terminal 20 , and also receives corrections to the latent skill information stored in the storage unit 16 from the individual user terminal 20 .

[0025] The memory unit 16 stores the trained model M. The trained model M is a machine learning or deep learning model. The trained model M is trained by a learning device (not shown) using skill information related to the skills of an individual user for training as training data for estimating latent skills. The skill information related to the skills of the individual user for training includes multiple skills possessed by the individual user. The learning device causes the trained model M to learn the associations between these multiple skills. As a result, when the trained model M receives skill information of an arbitrary individual user as input, it becomes able to estimate highly associated latent skills from the received skill information. The memory unit 16 also stores skill information, latent skill information, required skill information, and compatibility.

[0026] Next, a notification operation of the information processing device 10 according to the second embodiment will be described with reference to Fig. 4. Fig. 4 is a flowchart showing an example of a notification operation of the information processing device 10 according to the present embodiment.

[0027] First, the skill information acquisition unit 11 of the information processing device 10 acquires skill information of an individual user (step S101). The skill information acquisition unit 11 acquires the skill information from the individual user terminal 20 or the storage unit 16. Next, the latent skill estimation unit 12 estimates latent skill information from the skill information using the trained model M stored in the storage unit 16 (step S102). Here, the latent skill estimation unit 12 also determines the skill information that was primarily used when estimating the latent skill information. The latent skill estimation unit 12 stores the latent skill information and the skill information that was primarily used when estimating the latent skill information in the storage unit 16.

[0028] Next, the compatibility calculation unit 13 calculates the compatibility between the individual user and the corporate user by comparing at least one of the skill information and the potential skill information with the required skill information that the corporate user requests of the individual user (step S103).The compatibility calculation unit 13 stores the compatibility in the storage unit 16.

[0029] Next, the notification unit 14 determines whether the degree of matching is equal to or greater than a predetermined threshold (step S104). If the notification unit 14 determines that the degree of matching is equal to or greater than the predetermined threshold (YES in step S104), it notifies at least one of the individual user terminal 20 and the corporate user terminal 30 (step S105). Specifically, the notification unit 14 notifies at least one of the individual user terminal 20 and the corporate user terminal 30 of the skill information, latent skill information, required skill information, and degree of matching. The notification unit 14 also notifies the individual user terminal 20 of the skill information primarily used in estimating the latent skill information determined by the latent skill estimation unit 12. On the other hand, if the notification unit 14 determines that the degree of matching is not equal to or greater than the predetermined threshold (NO in step S104), it terminates the processing.

[0030] Next, a latent skill correction operation of the information processing device 10 according to the second embodiment will be described with reference to FIG. 5 . FIG. 5 is a flowchart showing an example of the latent skill correction operation of the information processing device 10 according to the present embodiment. First, the correction receiving unit 15 of the information processing device 10 transmits the latent skill information stored in the storage unit 16 to the personal user terminal 20 of the individual user (step S201). Next, the correction receiving unit 15 determines whether or not a request to correct the latent skill information has been received from the personal user terminal 20 (step S202). If the correction receiving unit 15 determines that a request to correct the latent skill information has been received from the personal user terminal 20 (YES in step S202), the correction receiving unit 15 corrects the stored latent skill information in accordance with the correction request. On the other hand, if the correction receiving unit 15 determines that a request to correct the latent skill information has not been received from the personal user terminal 20 (NO in step S202), the processing ends.

[0031] As described above, the information processing device 10 according to the second embodiment can estimate latent skill information of an individual user from the skill information of the individual user using a trained learning model. Therefore, the information processing device 10 can determine corporate users whose needs may potentially match those of the individual user. Furthermore, the information processing device 10 can determine corporate users whose needs may potentially match those of the individual user. For example, there is a shortage of engineers in society. In a matching service between corporate users and individual users, estimating the latent skills of individual users can identify people who are suited to being engineers, even if they are not currently engineers. Furthermore, this is expected to help resolve the shortage of engineers. Furthermore, by estimating latent skills, the information processing device 10 can enable corporate users or individual users to identify skills that individual users can acquire in a short period of time. Furthermore, corporate users can reduce costs for training, etc.

[0032] Furthermore, by calculating the degree of suitability, the information processing device 10 can introduce corporate users who are highly suitable to individual users, and can also introduce individual users who are highly suitable to corporate users.

[0033] Although the second embodiment has been described above, the configuration of the information processing device according to this embodiment is not limited to the above. For example, the information processing device 10 may not include the trained model M. In this case, the information processing device 10 may be communicably connected to a predetermined external terminal including the trained model M, and may realize the above-described functions by communicating with the external terminal.

[0034] With the above-described configuration, the present embodiment can provide an information processing device that can effectively connect individual users with the human resources that corporate users are looking for. Furthermore, the information processing device 10 can more effectively connect corporate users with individual users by accepting modifications to the latent skill information from the individual users.

[0035] (Third embodiment) Next, the configuration of an information processing device 40 according to a third embodiment will be described with reference to Fig. 6. Fig. 6 is a block diagram showing an example of the configuration of the information processing device 40 according to this embodiment. The information processing device 40 adds a required skill information acquisition unit 41 and a latent required skill estimation unit 42 to the configuration of the information processing device 10 according to the second embodiment. In addition, the compatibility calculation unit 13 and the storage unit 16 have the following additional functions.

[0036] The required skill information acquisition unit 41 acquires required skill information (required skill #1, required skill #2, required skill #3, . . . , required skill #N) which is the skills that a corporate user requests from an individual user.

[0037] The latent required skill estimation unit 42 uses the trained model L stored in the storage unit 16 to estimate latent required skill information related to skills that the corporate user potentially requires of the individual user from the acquired required skill information. The latent required skill information is at least one latent required skill that the corporate user potentially requires of the individual user (latent required skill #1, latent required skill #2, latent required skill #3, ... latent required skill #N). If the required skill information is, for example, C language skills and programming experience in the automotive industry, the latent required skill estimation unit 42 estimates embedded C language skills as the latent required skill information. The trained model L is a machine learning or deep learning model. The trained model L is trained by a learning device (not shown) using required skill information for learning as training data for estimating the latent required skill information.

[0038] The compatibility calculation unit 13 calculates the compatibility between the individual user and the corporate user by comparing at least one of the skill information and the latent skill information with at least one of the required skill information and the latent required skill information.

[0039] Next, a notification operation of the information processing device 40 according to the third embodiment will be described with reference to Fig. 7. Fig. 7 is a flowchart showing an example of a notification operation of the information processing device 40 according to the present embodiment.

[0040] First, the skill information acquisition unit 11 of the information processing device 40 acquires skill information of an individual user (step S301). The skill information acquisition unit 11 acquires the skill information from the individual user terminal 20 or the storage unit 16.

[0041] Next, the latent skill estimation unit 12 estimates latent skill information from the skill information using the trained model M stored in the storage unit 16 (step S302). Here, the latent skill estimation unit 12 also determines skill information that was mainly used when estimating the latent skill information. The latent skill estimation unit 12 stores the latent skill information and the skill information that was mainly used when estimating the latent skill information in the storage unit 16.

[0042] Next, the required skill information acquisition unit 41 acquires required skill information, which is the skills that the corporate user requests from the individual user (step S303). The required skill information acquisition unit 41 acquires the required skill information from the corporate user terminal 30 or the storage unit 16.

[0043] Next, the latent required skill estimation unit 42 estimates latent required skill information related to skills that the corporate user latently requires of the individual user from the acquired required skill information using the trained model L stored in the storage unit 16 (step S304). Here, the latent required skill estimation unit 42 also determines required skill information that was mainly used when estimating the latent required skill information. The latent required skill estimation unit 42 stores the latent required skill information and the required skill information that was mainly used when estimating the latent required skill information in the storage unit 16.

[0044] Next, the compatibility calculation unit 13 calculates the compatibility between the individual user and the corporate user by comparing at least one of the skill information and the potential skill information with at least one of the required skill information and the potential required skill information (step S305). The compatibility calculation unit 13 stores the compatibility in the storage unit 16.

[0045] Next, the notification unit 14 determines whether the degree of match is equal to or greater than a predetermined threshold (step S306). If the notification unit 14 determines that the degree of match is equal to or greater than the predetermined threshold (YES in step S306), it notifies at least one of the individual user terminal 20 and the corporate user terminal 30 (step S307). Specifically, the notification unit 14 notifies at least one of the individual user terminal 20 and the corporate user terminal 30 of the skill information, latent skill information, required skill information, and degree of match. The notification unit 14 also notifies at least one of the individual user terminal 20 and the corporate user terminal 30 of the skill information primarily used in estimating the latent skill information determined by the latent skill estimation unit 12. The notification unit 14 may also notify at least one of the individual user terminal 20 and the corporate user terminal 30 of the required skill information primarily used in estimating the latent required skill information. On the other hand, if the notification unit 14 determines that the degree of match is not equal to or greater than the predetermined threshold (NO in step S306), it terminates the process.

[0046] As described above, the information processing device 40 according to the third embodiment uses a trained learning model to estimate latent required skill information from required skill information. The information processing device 40 calculates the compatibility between an individual user and a corporate user using the latent required skill information. Therefore, by taking into account the latent requirements of a company, the information processing device 40 can more appropriately connect the talent required by the corporate user with the individual user.

[0047] Each component in the above-described embodiments may be configured with hardware or software, or both, and may be configured with a single piece of hardware or software, or may be configured with multiple pieces of hardware or software. Each device and each function (processing) may be realized by a computer 1000 having a processor 1001 such as a CPU (Central Processing Unit) and a memory 1002 serving as a storage device, as shown in Fig. 6. For example, a program for performing the method (video processing method) in the embodiment may be stored in the memory 1002, and each function may be realized by the processor 1001 executing the program stored in the memory 1002.

[0048] These programs include instructions (or software code) that, when loaded into a computer, cause the computer to perform one or more functions described in the embodiments. The programs may be stored on a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, computer-readable media or tangible storage media include random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technology, CD-ROM, digital versatile disc (DVD), Blu-ray disc or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The programs may also be transmitted on a transitory computer-readable medium or communication medium. By way of example and not limitation, transitory computer-readable media or communication media include electrical, optical, acoustic, or other forms of propagated signals.

[0049] The present disclosure is not limited to the above-described embodiment, and can be modified as appropriate within the scope of the present disclosure.

[0050] Some or all of the above embodiments may be described as, but are not limited to, the following supplementary notes. (Supplementary Note 1) An information processing device comprising: a skill information acquisition unit that acquires skill information related to the skills of an individual user; and a latent skill estimation unit that estimates latent skill information related to the latent skills of the individual user from the acquired skill information related to the skills of the individual user for learning, using a trained learning model that has been trained using the skill information related to the skills of the individual user as teacher data for estimating latent skills. (Supplementary Note 2) The information processing device according to Supplementary Note 1, wherein the skill information includes work history information indicating the work history of the individual user. (Supplementary Note 3) The information processing device according to Supplementary Note 1, further comprising a compatibility calculation unit that calculates a compatibility between the individual user and the corporate user by comparing the skill information and the latent skill information with required skill information that a corporate user requests of the individual user. (Supplementary Note 4) The information processing device according to Supplementary Note 3, further comprising a notification unit that notifies at least one of the individual user or the corporate user of the result of the comparison based on the compatibility. (Supplementary Note 5) The information processing device according to Supplementary Note 4, wherein the latent skill estimation unit determines the skill information mainly used when estimating the latent skill information, and the notification unit notifies the individual user of the skill information mainly used when estimating the determined latent skill information. (Supplementary Note 6) The information processing device according to Supplementary Note 1, further comprising: a required skill information acquisition unit that acquires required skill information that a corporate user requests of the individual user, and a latent required skill estimation unit that estimates latent required skill information related to skills that the corporate user latently requests of the individual user from the acquired required skill information using a trained learning model that has been trained using required skill information for learning as teacher data. (Supplementary Note 7) The information processing device according to Supplementary Note 6, further comprising a compatibility calculation unit that calculates a compatibility between the individual user and the corporate user by comparing the skill information and the latent skill information with the required skill information and the latent required skill information.(Supplementary Note 8) The information processing device according to Supplementary Note 7, further comprising a notification unit that notifies at least one of the individual user or the corporate user of the result of the matching based on the degree of compatibility. (Supplementary Note 9) The information processing device according to Supplementary Note 1, further comprising a correction receiving unit that presents the latent skill information to the individual user and receives corrections to the latent skill information from the individual user. (Supplementary Note 10) An information processing method in which a computer acquires skill information related to the skills of the individual user, and estimates latent skill information related to the individual user's latent skills from the acquired skill information using a trained learning model that has been trained to use skill information related to the skills of the individual user for learning as training data for estimating latent skills. (Supplementary Note 11) The information processing method according to Supplementary Note 10, in which the skill information includes work history information indicating the work history of the individual user. (Supplementary Note 12) The information processing method according to Supplementary Note 10, in which the computer further calculates the degree of compatibility between the individual user and the corporate user by comparing the skill information and the latent skill information with required skill information that the corporate user requests of the individual user. (Supplementary Note 13) The information processing method of Supplementary Note 12, wherein the computer further notifies at least one of the individual user or the corporate user of the matching result based on the degree of compatibility. (Supplementary Note 14) The information processing method of Supplementary Note 13, wherein the computer further determines the skill information that was primarily used when estimating the latent skill information, and notifies the individual user of the skill information that was primarily used when estimating the determined latent skill information. (Supplementary Note 15) The information processing method of Supplementary Note 10, wherein the computer further acquires required skill information that the corporate user requires of the individual user, and estimates latent required skill information related to skills that the corporate user potentially requires of the individual user from the acquired required skill information using a trained learning model trained using required skill information for learning as training data.(Supplementary Note 16) The information processing method of Supplementary Note 15, wherein the computer further calculates a degree of compatibility between the individual user and the corporate user by comparing the skill information and the latent skill information with the required skill information and the latent required skill information. (Supplementary Note 17) The information processing method of Supplementary Note 16, wherein the computer further notifies at least one of the individual user or the corporate user of the comparison result based on the degree of compatibility. (Supplementary Note 18) The information processing method of Supplementary Note 10, wherein the computer further presents the latent skill information to the individual user and accepts modifications to the latent skill information from the individual user. (Supplementary Note 19) A program causing a computer to execute a process of acquiring skill information related to the skills of an individual user, and estimating latent skill information related to the latent skills of the individual user from the acquired skill information using a trained learning model that has been trained to use skill information related to the skills of the individual user for learning as training data for estimating latent skills. (Supplementary Note 20) The program according to Supplementary Note 19, wherein the skill information includes work history information indicating the work history of the individual user. (Supplementary Note 21) The program according to Supplementary Note 19, further causing a computer to execute a process of calculating a degree of compatibility between the individual user and the corporate user by comparing the skill information and the latent skill information with required skill information that the corporate user requests of the individual user. (Supplementary Note 22) The program according to Supplementary Note 21, further causing a computer to execute a process of notifying at least one of the individual user or the corporate user of the result of the comparison based on the degree of compatibility. (Supplementary Note 23) The program according to Supplementary Note 22, further causing a computer to execute a process of determining the skill information that was primarily used when estimating the latent skill information, and notifying the individual user of the skill information that was primarily used when estimating the determined latent skill information.(Supplementary Note 24) The program according to Supplementary Note 19, further causing a computer to execute a process of acquiring required skill information that a corporate user requests of an individual user, and estimating latent required skill information related to skills that the corporate user potentially requests of the individual user from the acquired required skill information using a trained learning model trained using required skill information for learning as teacher data. (Supplementary Note 25) The program according to Supplementary Note 24, further causing a computer to execute a process of calculating a compatibility between the individual user and the corporate user by comparing the skill information and the latent skill information with the required skill information and the latent required skill information. (Supplementary Note 26) The program according to Supplementary Note 25, further causing a computer to execute a process of notifying at least one of the individual user or the corporate user of the result of the comparison based on the compatibility. (Supplementary Note 27) The program according to Supplementary Note 19, further causing a computer to execute a process of presenting the latent skill information to the individual user and accepting a modification of the latent skill information from the individual user.

[0051] Although the present invention has been described above with reference to the embodiments, the present invention is not limited to the above. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the invention.

[0052] This application claims priority based on Japanese Patent Application No. 2023-004995, filed on January 17, 2023, the disclosure of which is incorporated herein by reference in its entirety.

[0053] 10, 40, 100 Information processing device 11 Skill information acquisition unit 12 Latent skill estimation unit 13 Suitability calculation unit 14 Notification unit 15 Correction reception unit 16 Storage unit 20 Personal user terminal 30 Corporate user terminal 41 Required skill information acquisition unit 42 Latent required skill estimation unit 101 Skill information acquisition unit 102 Latent skill estimation unit 1000 Computer 1001 Processor 1002 Memory

Claims

1. A skill information acquisition means for acquiring skill information relating to the skills of individual users; and a latent skill estimation means for estimating latent skill information regarding the latent skills of the individual user from the acquired skill information regarding the skills of the individual user for learning, using a trained learning model trained as training data for estimating the latent skills. Information processing device.

2. The skill information is includes work history information indicating the work history of the individual user; The information processing device according to claim 1 .

3. The system further includes a compatibility calculation means for calculating a compatibility between the individual user and the corporate user by comparing the skill information and the potential skill information with required skill information that the corporate user requires of the individual user. The information processing device according to claim 1 .

4. The system further includes a notification unit that notifies at least one of the individual user and the corporate user of the result of the matching based on the degree of matching. The information processing device according to claim 3 .

5. The latent skill estimation means determining the skill information primarily used when estimating the latent skill information; The notification means The skill information that was primarily used when estimating the determined latent skill information is notified to the individual user. The information processing device according to claim 4 .

6. a required skill information acquisition means for acquiring required skill information that a corporate user requests from an individual user; Required skills information for learning and a potential required skill estimation means for estimating potential required skill information relating to skills that the corporate user potentially requires of the individual user from the acquired required skill information using a trained learning model that has been trained as training data. The information processing device according to claim 1 .

7. The system further includes a compatibility calculation means for calculating a compatibility between the individual user and the corporate user by comparing the skill information and the potential skill information with the required skill information and the potential required skill information. The information processing device according to claim 6 .

8. The system further includes a notification unit that notifies at least one of the individual user and the corporate user of the result of the matching based on the degree of matching. The information processing device according to claim 7 .

9. The computer Obtain skill information about the skills of individual users; Using a trained learning model that has been trained using skill information related to the skills of an individual user for learning as training data for estimating latent skills, latent skill information related to the latent skills of the individual user is estimated from the acquired skill information. Information processing methods.

10. Obtain skill information about the skills of individual users; A computer is caused to execute a process of estimating latent skill information regarding the latent skills of an individual user from the acquired skill information, using a trained learning model that has been trained as training data for estimating latent skills. program.