Information processing device, information processing method, and information processing program

Abstract

An acquisition unit according to the present invention acquires communication history information indicating the status of communication between a plurality of persons. An estimation unit estimates the relationship between the plurality of persons using the communication history information acquired by the acquisition unit. An update unit updates relationship network information indicating the relationship between the plurality of persons by using the relationship between the plurality of persons estimated by the estimation unit.

Description

Information processing device, information processing method, and information processing program

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

[0002] In order to effectively utilize existing human resources within an organization such as a company, technologies related to so-called "know-who" systems have been provided. For example, a service has been provided that uses AI (artificial intelligence) to extract pre-registered technical keywords from emails and chat messages, and builds a human resources database that accumulates employee technical and knowledge information (see Non-Patent Document 1). Also, a service has been provided that matches employees based on specified conditions (see Non-Patent Document 2).

[0003] Hitachi Solutions Create, Ltd., Human Resources and Skills Matching Service [online], [Retrieved July 5, 2024], Internet <URL: https: / / www.hitachi-solutions-create.co.jp / solution / skills_matching / > Three Corporation, Three for Business [online], [Retrieved July 5, 2024], Internet <URL: https: / / three-biz.com>

[0004] However, there is room for improvement in the conventional technology. For example, while the above conventional technology allows a user to grasp the skills and knowledge information of multiple people, such as company employees, and to search for contacts based on user-specified criteria, it does not take into account the relationships between the multiple people. Therefore, even if a user among multiple people can search for other people who have desired knowledge by specifying criteria, that knowledge may not be effectively utilized depending on the relationship between the user and the other people. Therefore, it is desirable to be able to appropriately grasp the relationships between multiple people.

[0005] The present invention has been made in view of the above, and has an object to make it possible to appropriately grasp the relationships between multiple people.

[0006] In order to solve the above-mentioned problems and achieve the object, the information processing device of the present invention is characterized by having an acquisition unit that acquires communication history information indicating the communication status between multiple people, an estimation unit that estimates the relationships between the multiple people using the communication history information acquired by the acquisition unit, and an update unit that updates relationship network information that indicates the relationships between the multiple people using the relationships between the multiple people estimated by the estimation unit.

[0007] According to the present invention, it is possible to appropriately grasp the relationships between a plurality of people.

[0008] FIG. 1 is a diagram showing an example of an outline of processing in an information processing system. FIG. 2 is a diagram showing an example of the configuration of an information processing system according to an embodiment. FIG. 3 is a diagram showing an example of the configuration of an information processing device according to an embodiment. FIG. 4 is a diagram for explaining an outline of information processing. FIG. 5 is a flowchart showing an example of a processing procedure executed by the information processing system. FIG. 6 is a diagram showing an example of a computer that executes an information processing program. FIG. 7 is a diagram showing an example of a problem in the prior art.

[0009] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. Note that the present invention is not limited to this embodiment. In addition, in the description of the drawings, the same parts are designated by the same reference numerals.

[0010] [Embodiment] [Overview] First, before describing information processing executed by an information processing system 1 (see FIG. 2) according to an embodiment, an overview and problems with existing technologies will be briefly described. In order to solve tasks in a huge group (organization) including a large number of people, there is a demand for matching people within the group (organization) to utilize the knowledge of the group, and various matching methods have been proposed. However, in matching, while the relationship between one person and another person (the other party) is important, the relationship is fluid, and it may not be possible to perform matching that takes recent relationships into consideration.

[0011] For example, when matching user X with one of other users A to D as shown in FIG. 7, it may be difficult to perform appropriate matching using conventional technology. FIG. 7 is a diagram showing an example of a problem with conventional technology. FIG. 7 shows a case where user A is the most knowledgeable about the knowledge (information) that user X is seeking. Therefore, when matching is performed simply based on the knowledge (information) that user X is seeking, as in existing services, user A is selected.

[0012] Such existing Know-Who services (searching for people who have knowledge of technology, knowledge, and know-how) do not take into consideration the relationship with the user, and it may be difficult to perform appropriate matching. For example, in the example of Figure 7, the communication situation between user A and user X is not suitable for user X to receive support from user A, and even if user X is matched with user A, it is difficult for user X to receive appropriate support from user A.

[0013] On the other hand, when searching for a partner after specifying matching conditions by oneself, the user may narrow down the options by himself / herself, making it difficult to perform appropriate matching. For example, in the example of Figure 7, when user X simply matches with a close friend, user X specifies close friend user C, and user C is selected. In this case, even though there may be a user more suitable than user C for user X to receive support from, user X simply matches with a close friend, and user X may be able to receive more appropriate support.

[0014] As such, there is room for improvement in existing services. For example, if it were possible to properly grasp the relationships between multiple people, such as the above-mentioned multiple users A to D, X, etc., it would be possible to perform appropriate matching based on the grasped relationships between multiple people.

[0015] Therefore, the information processing system 1 executes processing to enable appropriate understanding of the relationships between multiple people. For example, the information processing system 1 estimates the relationships between multiple people based on the state of communication between the multiple people, and generates (updates) relationship network information indicating the relationships between the multiple people using the estimated relationships between the multiple people. In this way, if the information processing system 1 can construct a relationship network that visualizes the relationships between multiple people, it becomes possible to appropriately understand the relationships between multiple people, and appropriate matching can be performed based on the understood relationships between multiple people.

[0016] An example of an overview of information processing executed by the above-described information processing system 1 will now be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of an overview of processing by the information processing system. Fig. 1 illustrates an example of a case in which relationships between user X and other users A to D are estimated based on communication between user X and other users A to D, and relationship network information is updated.

[0017] In the following, chat information relating to chats exchanged between users will be described as an example of information indicating the status of communication (also referred to as "communication history information"). Note that the communication history information is not limited to chat information, and may include any information relating to communication between users, such as email information relating to emails sent and received between users, message information exchanged between users via a message service, and speech information in conversations between users.

[0018] 1, the information processing system 1 estimates the relationship between user X and each of other users A to D. For example, the information processing system 1 estimates a target (also referred to as an "estimated target") related to the content of communication between user X and each of other users A to D based on chat information exchanged between user X and each of other users A to D.

[0019] In FIG. 1 , the information processing system 1 estimates four estimation targets: "work-related topics" indicated by "1)" in FIG. 1 , "non-work-related topics" indicated by "2)" in FIG. 1 , "positive / negative topics" indicated by "3)" in FIG. 1 , and "support for others" indicated by "4)" in FIG. 1 . For example, the information processing system 1 estimates the amount of "work-related topics" and "non-work-related topics," estimates which tendency is stronger for "positive / negative topics," and estimates whether "support for others" is positive or negative. Note that the above estimation targets are merely examples, and the information processing system 1 may estimate various information related to relationships between users. For example, the information processing system 1 may estimate whether the tendency is stronger for work-related topics or non-work-related topics using "work-related topics / non-work-related topics" as estimation targets.

[0020] The information processing system 1 estimates "work-related topics," "non-work-related topics," "positive / negative topics," and "support for others" for user A based on chat information exchanged between user X and user A. In FIG. 1 , the information processing system 1 estimates that the relationship between user X and user A has very few "work-related topics," very few "non-work-related topics," negative "positive / negative topics," and a negative "support for others."

[0021] Furthermore, the information processing system 1 estimates that the relationship between user X and user B involves a large number of "work-related topics," a small number of "non-work-related topics," negative "positive / negative topics," and a negative attitude toward "supporting others." The information processing system 1 estimates that the relationship between user X and user C involves a small number of "work-related topics," a large number of "non-work-related topics," positive "positive / negative topics," and a positive attitude toward "supporting others." The information processing system 1 estimates that the relationship between user X and user D involves a small number of "work-related topics," a small number of "non-work-related topics," positive "positive / negative topics," and a very positive attitude toward "supporting others."

[0022] The information processing system 1 uses the relationships between user X and each of the other users A to D to update the relationship network information RN1 indicating the relationships between user X and each of the other users A to D. For example, the information processing system 1 updates the relationship network information RN1 indicating the relationships between users by increasing or decreasing the relationship distance indicating the relationships between users. Note that the larger the value of the relationship distance, the closer the relationship between the two people, i.e., the more intimate the relationship between the two people, and the smaller the value, the further the relationship between the two people, i.e., the more distant the relationship between the two people.

[0023] 1 , the information processing system 1 estimates that the relationship between user X and user A involves very little communication (topics, etc.), both work-related and non-work-related, that the topics are negative, and that user A is reluctant to support others, and therefore updates the relationship between user X and user A to distance them. For example, the information processing system 1 estimates that the relationship between user X and user A is distant because the communication (topics, etc.) between user X and user A is negative, and updates the relationship between user X and user A to distance them. The information processing system 1 updates the relationship network information RN1 by decreasing (negating) the relationship distance between user X and user A.

[0024] Furthermore, the information processing system 1 estimates that the relationship between user X and user B involves a large amount of communication (topics, etc.) related to work, little communication (topics, etc.) other than work, the topics are negative, and user B's support for others is negative, so it updates the relationship between user X and user B to distance them. For example, the information processing system 1 estimates that the relationship between user X and user B is distant because the communication (topics, etc.) between user X and user B is negative, and updates the relationship between user X and user B to distance them.

[0025] The information processing system 1 updates the relationship network information RN1 by decreasing (negating) the relationship distance between user X and user B. For example, since there is more communication between user X and user B than between user X and user A, the amount of decrease in the relationship distance between user X and user B is set to be smaller than the amount of decrease in the relationship distance between user X and user A. Note that the amount of decrease may be determined using any information as appropriate; for example, the amount of decrease in the relationship distance may be determined taking into account information such as support for others.

[0026] Furthermore, the information processing system 1 estimates that the relationship between user X and user C involves little work-related communication (topics, etc.), a great deal of non-work-related communication (topics, etc.), positive topics, and a positive attitude toward supporting others, and therefore updates the relationship between user X and user C to bring them closer together. For example, the information processing system 1 estimates that the relationship between user X and user C is close because the communication (topics, etc.) between user X and user C is positive, and updates the relationship between user X and user C to bring them closer together. The information processing system 1 updates the relationship network information RN1 by increasing (positively increasing) the relationship distance between user X and user C.

[0027] Furthermore, the information processing system 1 estimates that the relationship between user X and user D involves little communication (topics, etc.) related to work, little communication (topics, etc.) other than work, the topics are positive, and user D's support for others is very proactive, and therefore updates the relationship between user X and user D to bring them closer together. For example, the information processing system 1 estimates that the relationship between user X and user D is close because the communication (topics, etc.) between user X and user D is positive, and updates the relationship between user X and user D to bring them closer together.

[0028] The information processing system 1 updates the relationship network information RN1 by increasing (increasing) the relationship distance between user X and user D. For example, because communication between user X and user D is less than communication between user X and user C, the increase in the relationship distance between user X and user D is set to be smaller than the increase in the relationship distance between user X and user C. Note that the increase may be determined using any information as appropriate; for example, the increase in the relationship distance may be determined taking into account information such as support for others.

[0029] In this way, the information processing system 1 estimates recent relationships based on the content of user communication (conversations, etc.), thereby updating the relationship network between people. Therefore, the information processing system 1 can appropriately grasp the relationships between multiple people.

[0030] For example, the information processing system 1 can estimate recent relationships and update the relationship network, making it possible to use it for matching according to the purpose at any given time. As described above, the information processing system 1 functions as a human network variation system based on the status of communication (conversation, etc.). Note that the relationship distance described above is merely one example of a relationship, and the relationship is not limited to the relationship distance, and may be various attribute values ​​(other attribute values) related to the relationship, such as the number of posts by each user or the number of times each user has supported others.

[0031] This allows the information processing system 1 to utilize information that enables appropriate understanding of relationships between multiple people for purpose-specific matching. For example, the information processing system 1 may provide the updated relationship network information to a matching service device that provides a matching service by transmitting updated relationship network information to the matching service device. In this case, the matching service device may provide a matching service using the relationship network information updated by the information processing system 1, thereby utilizing the information that enables appropriate understanding of relationships between multiple people for purpose-specific matching.

[0032] Furthermore, for example, the information processing system 1 may provide a matching service using the updated relationship network. For example, the information processing system 1 may provide a matching service using the updated relationship network information and a Know-Who list, which is list information indicating the skills, knowledge, know-how, etc. possessed by each user.

[0033] [Configuration of Information Processing System] Next, an example of an information processing system 1 that executes the above-described information processing will be described with reference to FIG. 2. FIG. 2 is a diagram showing an example configuration of an information processing system according to an embodiment. Note that the system configuration shown in FIG. 2 is merely an example, and the information processing system 1 can adopt any device configuration as long as it can execute the desired processing. Furthermore, for processes described as being performed by the information processing system 1, any device capable of executing that processing, such as the information processing device 100, may perform the process, depending on the device configuration of the information processing system 1.

[0034] As shown in Fig. 2, the information processing system 1 includes an input device 10, an output device 20, an external service device 50, and an information processing device 100. The information processing device 100 is communicably connected to the input device 10, the output device 20, and the external service device 50 via a predetermined network N, either wired or wirelessly. Fig. 2 is a diagram showing an example configuration of an information processing system according to an embodiment. Note that the information processing system 1 shown in Fig. 2 may include a plurality of input devices 10, a plurality of output devices 20, a plurality of external service devices 50, and a plurality of information processing devices 100.

[0035] The input device 10 is an information processing device (computer) used to input information. The input device 10 may be a device used to acquire information from the information processing device 100. For example, the input device 10 may be a device used to read information used by the information processing device 100 for processing. For example, the input device 10 may acquire, from the external service device 50, communication history information that indicates the status of communication between users and that is held by the external service device 50, and transmit the acquired communication history information to the information processing device 100.

[0036] For example, the input device 10 may be a device into which information regarding communication between users is input. For example, the input device 10 is a device that collects information regarding communication between users. In this case, the input device 10 associates the collected information regarding communication between users as communication history information indicating the status of the communication between users with information identifying the user who performed the communication (such as a user ID), and transmits the information to the information processing device 100. For example, the input device 10 may be a device having a sensor that detects the user's speech. The input device 10 may be, for example, a terminal device used by a user, such as a smartphone or a tablet terminal.

[0037] The output device 20 is an information processing device (computer) used to output information. The output device 20 outputs information provided by the information processing device 100. For example, the output device 20 may have a display device (such as a display) that displays the information provided by the information processing device 100, or may have an audio output device (such as a speaker) that outputs the information provided by the information processing device 100 as audio.

[0038] The output device 20 outputs relationship network information indicating the relationships between multiple people provided from the information processing device 100. The output device 20 displays the relationship network information indicating the relationships between multiple people. For example, the output device 20 may be a device used by an administrator of the information processing system 1. The output device 20 may also be a terminal device used by a user, such as a smartphone or a tablet terminal. For example, the output device 20 may be integrated with the input device 10.

[0039] The external service device 50 is an information processing device (computer) used to provide services to users, etc. For example, the external service device 50 may be a server device, etc. used to provide external services such as communication tools. The external service device 50 is a service providing device that provides communication services such as dialogue (conversation) and message exchange (chat, etc.) between users.

[0040] For example, the external service device 50 stores information about communication between users that occurred in a communication service as communication history information that indicates the status of the communication between those users. For example, the external service device 50 stores information exchanged in communication in a communication service as communication history information in association with information that identifies the users who performed the communication (such as a user ID). For example, the external service device 50 stores chat information between users that occurred in the communication service as communication history information that indicates the status of the communication between those users.

[0041] The information processing device 100 is a computer that constructs (generates) relationship network information indicating the relationships between multiple users based on communications that have occurred between the multiple users. The information processing device 100 estimates the relationships between the multiple users using communication history information that indicates the status of communication between the multiple users. For example, the information processing device 100 analyzes the status of communication (conversations, etc.) to estimate the relationships. The information processing device 100 generates (updates) relationship network information between the multiple users using the estimated relationships between the multiple users. For example, the information processing device 100 is a determination device that executes various determination processes.

[0042] For example, the information processing device 100 analyzes the status of communication (conversations, etc.) within a group such as a workplace to estimate recent relationships and update the relationship network information. The information processing device 100 estimates recent relationships from the status of users' communication (conversations, etc.), such as the content of their communication (conversations, etc.), and updates the relationship network, thereby enabling it to be used for matching according to the purpose. For example, the information processing device 100 provides relationship network information of multiple users to a service providing device (such as the external service device 50), thereby enabling the service providing device to provide a matching service using the relationship network information of multiple users.

[0043] [Configuration of Information Processing Apparatus] Next, a configuration of the information processing apparatus 100, which is an example of an information processing apparatus that executes information processing according to the embodiment, will be described. Fig. 3 is a diagram showing an example of the configuration of the information processing apparatus 100 according to the embodiment.

[0044] 3, the information processing device 100 of this embodiment is realized by a general-purpose computer such as a personal computer, and includes a communication unit 110, a storage unit 120, and a control unit 130. The information processing device 100 may also include an input unit (e.g., a keyboard, a mouse, etc.) that accepts various operations from an administrator of the information processing device 100, a display unit (e.g., a liquid crystal display, etc.) that displays information, an audio output unit (e.g., a speaker, etc.) that outputs information as audio, etc.

[0045] The communication unit 110 is realized by, for example, a network interface card (NIC), etc. The communication unit 110 is connected to a predetermined network such as the Internet via a wired or wireless connection, and transmits and receives information to and from other information processing devices such as the input device 10, the output device 20, and the external service device 50.

[0046] The storage unit 120 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in FIG. 3 , the storage unit 120 according to the embodiment includes a history information storage unit 121, a parameter information storage unit 122, and a relationship network information storage unit 123.

[0047] The history information storage unit 121 according to the embodiment stores history information related to communication between multiple people. The history information storage unit 121 stores various pieces of information that the information processing device 100 receives from external information processing devices. For example, the history information storage unit 121 stores various pieces of information that the information processing device 100 receives from the input device 10.

[0048] The history information storage unit 121 stores communication history information indicating the status of communication between multiple people. The history information storage unit 121 stores communication history information related to communication between users. For example, the history information storage unit 121 stores communication history information including chat information, which is history information (chat history) of chats exchanged between users.

[0049] For example, the history information storage unit 121 stores communication history information including mail information related to emails sent and received between users. For example, the history information storage unit 121 stores communication history information including message information exchanged between users via a message service. For example, the history information storage unit 121 stores communication history information including user utterance information in conversations between users.

[0050] The history information storage unit 121 is not limited to the above, and may store various types of information depending on the purpose.

[0051] The parameter information storage unit 122 according to the embodiment stores information related to parameters. The parameter information storage unit 122 functions as a parameter storage DB. For example, the parameter information storage unit 122 stores information indicating relationship parameters.

[0052] The parameter information storage unit 122 stores the classification results of the content of communication between multiple people included in the communication history information. For example, the parameter information storage unit 122 stores parameters based on the classification results of the content of communication between multiple people included in the communication history information.

[0053] The parameter information storage unit 122 stores information indicating the relationships between a plurality of people estimated using the communication history information. The parameter information storage unit 122 stores information indicating the relationships between a plurality of people estimated based on the classification results of the content of communication.

[0054] The parameter information storage unit 122 is not limited to the above, and may store various types of information depending on the purpose.

[0055] The relationship network information storage unit 123 according to the embodiment stores various types of information related to relationships between people. The relationship network information storage unit 123 stores information for visualizing relationships between people.

[0056] The relationship network information storage unit 123 stores relationship network information indicating relationships between multiple people. For example, the relationship network information storage unit 123 stores relationship network information updated using the relationships between multiple people.

[0057] The relationship network information storage unit 123 is not limited to the above, and may store various types of information depending on the purpose.

[0058] Furthermore, the above is merely an example, and the storage unit 120 may store various information other than the above. For example, the storage unit 120 may store various information used by the information processing device 100 for processing. For example, the storage unit 120 may store keyword list information used to classify the content of communication. Furthermore, when the information processing system 1 provides a matching service using an updated relationship network, the storage unit 120 stores a know-who list (list information) that indicates information (technology, knowledge, know-how, etc.) possessed by each user.

[0059] Returning to Fig. 3 , the explanation will be continued. The control unit 130 is realized, for example, by a processor such as a CPU (Central Processing Unit) executing a program (e.g., an information processing program) stored inside the information processing device 100 using a RAM or the like as a work area. The control unit 130 is also realized, for example, by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). As shown in Fig. 3 , the control unit 130 includes an input data acquisition unit 131, a parameter extraction unit 132, a parameter estimation unit 133, a network update unit 134, and an output unit 135.

[0060] The input data acquisition unit 131 executes an acquisition process to acquire information. The input data acquisition unit 131 functions as an acquisition unit that acquires information.

[0061] For example, the input data acquisition unit 131 acquires various information from the storage unit 120. For example, the input data acquisition unit 131 acquires information from the history information storage unit 121, the parameter information storage unit 122, and the relationship network information storage unit 123.

[0062] The input data acquisition unit 131 receives various types of information from external information processing devices such as the input device 10 and the external service device 50. For example, the input data acquisition unit 131 acquires information input to the input device 10 from the input device 10. For example, the input data acquisition unit 131 acquires information held by the external service device 50 from the external service device 50.

[0063] The input data acquisition unit 131 acquires communication history information indicating the status of communication between multiple people. For example, the input data acquisition unit 131 reads various data from the input device 10. For example, the input data acquisition unit 131 reads chat information for a certain period of time from an external service device 50 such as a communication tool, triggered by regular or manual execution.

[0064] The parameter extraction unit 132 executes an extraction process to extract information. For example, the parameter extraction unit 132 extracts information from various types of information stored in the storage unit 120. For example, the parameter extraction unit 132 extracts information from various types of information stored in the history information storage unit 121, the parameter information storage unit 122, or the relationship network information storage unit 123.

[0065] For example, the parameter extraction unit 132 extracts information from various types of information acquired from an external information processing device such as the input device 10 or the external service device 50. For example, the parameter extraction unit 132 extracts information from various types of information acquired by the input data acquisition unit 131. The parameter extraction unit 132 generates various types of information using the extracted information. The parameter extraction unit 132 calculates various types of information using the extracted information. The parameter extraction unit 132 executes an analysis process using the various types of information acquired by the input data acquisition unit 131.

[0066] The parameter extraction unit 132 executes a classification process to classify information. The parameter extraction unit 132 functions as a classification unit that classifies information. The parameter extraction unit 132 classifies the content of communication between multiple people included in the communication history information. For example, the parameter extraction unit 132 classifies the content of communication between multiple people by analyzing communication history information including text information such as chat information and utterance information converted from user utterances into text.

[0067] For example, the parameter extraction unit 132 classifies the content of communication between multiple people by analyzing communication history information (text information, etc.) that indicates the content of communication that occurred between multiple people. For example, the parameter extraction unit 132 classifies the content of communication between multiple people by analyzing the content appropriately using natural language processing technology such as morphological analysis. Note that the above is merely an example, and the parameter extraction unit 132 may perform processing to classify the content of communication using any method as long as it is possible to classify the content of communication.

[0068] For example, the parameter extraction unit 132 classifies the content of the chat information obtained by the input data acquisition unit 131. For example, the parameter extraction unit 132 classifies the content of communication between multiple users included in communication history information such as chat information into whether it is related to work or not.

[0069] For example, the parameter extraction unit 132 determines (classifies) whether the content of the communication is work-related or unrelated based on keywords included in communication history information such as chat information. For example, the parameter extraction unit 132 classifies the content of the communication as work-related or unrelated using keyword list information in which each keyword is associated with information indicating whether the keyword is work-related or unrelated.

[0070] For example, the parameter extraction unit 132 classifies the content of communication between a plurality of users included in communication history information such as chat information into positive or negative.

[0071] For example, the parameter extraction unit 132 determines (classifies) whether the content of the communication was positive or native based on keywords included in communication history information such as chat information. For example, the parameter extraction unit 132 classifies whether the content of the communication was positive or native using keyword list information in which each keyword is associated with information indicating whether the keyword is positive or native.

[0072] Note that the above is merely an example, and the parameter extraction unit 132 may classify the content of communication using various information as appropriate. Furthermore, the parameter extraction unit 132 may perform various classifications other than those described above. For example, the parameter extraction unit 132 derives (classifies) attribute values ​​such as the number of communications (number of posts, etc.) between multiple users and the number of times each user has supported others, which are included in communication history information such as chat information. The parameter extraction unit 132 updates the information stored in the parameter information storage unit 122 based on the classification results.

[0073] The parameter estimation unit 133 executes an estimation process to estimate information. The parameter estimation unit 133 functions as an estimation unit that estimates information. The parameter estimation unit 133 executes the estimation process based on various pieces of information stored in the storage unit 120. For example, the parameter estimation unit 133 executes the estimation process based on various pieces of information stored in the history information storage unit 121, the parameter information storage unit 122, and the relationship network information storage unit 123.

[0074] The parameter estimation unit 133 performs estimation processing based on various pieces of information acquired from an external information processing device such as the input device 10 or the external service device 50. The parameter estimation unit 133 estimates various pieces of information using the information acquired by the input data acquisition unit 131. The parameter estimation unit 133 estimates various pieces of information using the information extracted by the parameter extraction unit 132. The parameter estimation unit 133 performs determination processing. For example, the parameter estimation unit 133 determines whether or not to perform processing.

[0075] The parameter estimation unit 133 estimates the relationships between multiple people by using the communication history information acquired by the input data acquisition unit 131. The parameter estimation unit 133 estimates the relationships between multiple people based on the classification result of the communication content by the parameter extraction unit 132.

[0076] The parameter estimation unit 133 tally up communications between multiple users included in the communication history information based on the classification result by the parameter extraction unit 132. The parameter estimation unit 133 tally up (estimates) information on each of work-related communications and non-work-related communications. For example, the parameter estimation unit 133 calculates the ratio of the number of work-related communications to the number of non-work-related communications among the communications between each user.

[0077] The parameter estimation unit 133 tally (estimates) information on each of positive communication and negative communication. For example, the parameter estimation unit 133 calculates the ratio of the number of positive communications to the number of negative communications in communications between users.

[0078] Note that the above is merely an example, and the parameter estimation unit 133 may estimate various pieces of information by appropriately using various pieces of information. Furthermore, the parameter estimation unit 133 may estimate various pieces of information other than the above. For example, the parameter estimation unit 133 counts (estimates) the number of communications (number of posts, etc.) between multiple users included in communication history information such as chat information, the number of times each user supports others, and the like. The parameter estimation unit 133 updates the information stored in the parameter information storage unit 122 based on the counted (estimated) results.

[0079] The network update unit 134 executes an update process to update information. The network update unit 134 functions as an update unit that updates information. The network update unit 134 updates relationship network information indicating the relationships between multiple people, using the relationships between multiple people estimated by the parameter estimation unit 133. The network update unit 134 updates relationship network information indicating the relationships between multiple people, using the relationships between multiple people based on the classification of communication content.

[0080] The network update unit 134 executes a generation process to generate information. For example, if relationship network information has not been generated, the network update unit 134 generates the relationship network information. For example, the network update unit 134 updates the information using various information stored in the storage unit 120. For example, the input data acquisition unit 131 updates the information using various information stored in the history information storage unit 121, the parameter information storage unit 122, and the relationship network information storage unit 123.

[0081] For example, the network update unit 134 updates the information using various information acquired from external information processing devices such as the input device 10 and the external service device 50. For example, the network update unit 134 updates the information using various information acquired by the input data acquisition unit 131. The network update unit 134 updates the information using information extracted by the parameter extraction unit 132. The network update unit 134 updates the information using information estimated by the parameter estimation unit 133.

[0082] The network update unit 134 updates the relationship network, such as the relationship distance and other attribute values, based on the estimation result (aggregation result) by the parameter estimation unit 133. For example, if the number of positive comments in communication between users is greater than the number of negative comments, the network update unit 134 shortens the relationship distance between those users (for example, by adding 1). For example, if the number of negative comments in communication between users is greater than the number of positive comments, the network update unit 134 lengthens the relationship distance between those users (for example, by subtracting 1).

[0083] If the number of positive communications between users is greater than the number of negative communications, and the number of communications (number of posts) is greater in the current update (Nth time) than in the previous update (N-1th time), the network update unit 134 will further shorten the relationship distance between the users (for example, by adding 1).

[0084] Note that the above is merely an example, and the network update unit 134 may update various pieces of information using various pieces of information as appropriate. Furthermore, the network update unit 134 may update various pieces of information other than the above. The network update unit 134 updates other attribute values. For example, the network update unit 134 updates information indicating whether communication between users is related to business, such as 80% business and 20% non-business. The network update unit 134 updates information indicating the number of times each user has been assisted, such as 10 times assistance. The network update unit 134 updates the information stored in the relationship network information storage unit 123 based on the update results.

[0085] The output unit 135 executes an output process to output various types of information. The output unit 135 provides information by outputting information to an external information processing device. The output unit 135 provides information to the external information processing device. The output unit 135 transmits information to the external information processing device. For example, the output unit 135 transmits various types of information to the output device 20.

[0086] The output unit 135 transmits the result of the estimation process to the outside via the communication unit 110. The output unit 135 controls the output device 20 to output the result of the estimation process by transmitting the result of the estimation process to the output device 20. For example, the output unit 135 transmits the result of the estimation process to the output device 20 and causes the output device 20 to output the result of the estimation process.

[0087] The output unit 135 outputs the relationship network generated (updated) by the network update unit 134. The output unit 135 transmits information to the output device 20, causing the output device 20 to output the transmitted information. The output unit 135 transmits the relationship network to the output device 20, and causes the output device 20 to display the relationship network, thereby outputting the relationship network.

[0088] Furthermore, for example, when the information processing system 1 provides a matching service using an updated relationship network, the information processing device 100 may have a matching unit. In this case, the matching unit may match users using the relationship network information updated by the network update unit 134 and a Know-Who list indicating information held by each user stored in the storage unit 120.

[0089] For example, the input data acquisition unit 131 acquires matching condition information indicating matching conditions, such as conditions for specifying users to be matched. Then, the matching unit performs user matching based on the matching condition information, using relationship network information and the Know-Who list. For example, the matching unit selects a user (also referred to as a "matching user") to be matched with the user requesting matching (also referred to as a "target user") based on the relationship with the target user and required information.

[0090] For example, the matching unit selects, as a matching user for the target user, a user who has the best relationship with the target user among users who have the required information indicated by the matching condition information. For example, the matching unit selects, as a matching user for the target user, a user who has the closest relationship with the target user among users who have the required information indicated by the matching condition information.

[0091] [Processing Example] Based on the above-described content, a processing example will now be described. For example, the information processing system 1 executes processing including steps #1 to #4 as shown below.

[0092] Step #1: Set the relationship distance between two people (between each user) to 0 as the initial value. (When updating for the Nth time, the value at the N-1th time is set as the initial value.)

[0093] Step #2: Categorize and aggregate the content of conversations between users from the chat history of the communication tool using steps #2-1 and #2-2, etc. Step #2-1: Extract chat history for a certain period (such as the past month). Step #2-2: Categorize the content of conversations into categories such as "work-related / not work-related" and "positive / negative," and aggregate the percentages. Also, count other relationship attribute values ​​(such as "number of posts" and "number of times supported by others"), etc. For example, estimate (aggregate) the following information: [80% work, 20% non-work], [90% positive, 10% negative], [150 posts], [10 supports].

[0094] Step #3: Update the "relationship distance" according to the aggregation results. The larger the value of the relationship distance, the closer (the stronger the connection). For example, if [positive > negative], increase the relationship distance (+1, etc.), and if [positive < negative], decrease the relationship distance (-1, etc.). Also, for example, if [positive > negative] and the number of posts is [Nth time > N-1th time], increase the relationship distance further (+1, etc.).

[0095] Step #4: Update the "other attribute values" according to the aggregation results. For example, update to [80% work, 20% non-work] or [10 times of support].

[0096] An outline of the processing using the above-described method is shown in Fig. 4. Fig. 4 is a diagram for explaining the outline of information processing. Note that explanations of points similar to those explained in Fig. 1 and the like will be omitted as appropriate. For example, Fig. 4 shows a case where, as shown in the processing outline PH1, the relationship between three users X, A, and B is estimated and the relationship distance is updated.

[0097] 4, the relationship between user X and user A has a communication (topics, etc.) ratio of 80% business and 20% business, a communication (topics, etc.) ratio of 90% positive and 10% negative, and the number of posts has increased since the previous time. Therefore, the information processing system 1 estimates that the relationship between user X and user A is good, and updates the relationship network information to shorten the relationship distance between user X and user A. For example, the information processing system 1 increases the relationship distance between user X and user A by 2, updating it from 2 to 4.

[0098] Furthermore, the relationship between User X and User B has a communication (topics, etc.) ratio of 90% business and 10% business, a communication (topics, etc.) ratio of 40% positive and 60% negative, and the number of posts has increased since the previous time. Therefore, the information processing system 1 estimates that the relationship between User X and User B is not good, and updates the relationship network information to increase the distance. For example, the information processing system 1 decreases the relationship distance between User X and User B by 1, updating it from 1 to 0.

[0099] Furthermore, the relationship between user A and user B has a communication (topics, etc.) ratio of 70% business and 30% business, a communication (topics, etc.) ratio of 80% positive and 20% negative, and the number of posts is lower than the previous time. Therefore, the information processing system 1 estimates that the relationship between user A and user B is good, and updates the relationship network information to shorten the distance. For example, the information processing system 1 increases the relationship distance between user A and user B by 1, updating it from 1 to 2.

[0100] In this way, the information processing system 1 updates the relationship network and utilizes, for example, the relationship distance and other attribute values ​​for matching. For example, when the information processing system 1 performs matching processing, the information processing system 1 performs matching processing by avoiding matching with people with a small relationship distance and matching with people who have provided support many times.

[0101] [Flowchart] An example of a processing procedure executed by the information processing system will now be described with reference to Fig. 5. Fig. 5 is a flowchart showing an example of a processing procedure executed by the information processing system 1. Note that the information processing system 1 executes the processing shown in Fig. 5 at any timing, such as periodically or manually.

[0102] The information processing system 1 reads chat information (step S101). For example, the input data acquisition unit 131 reads the chat information from an external service IS such as a communication tool.

[0103] The information processing system 1 classifies the content (step S102). For example, the parameter extraction unit 132 classifies the content of communication between a plurality of users included in communication history information such as chat information.

[0104] The information processing system 1 tally the classification results (step S103). For example, the parameter estimation unit 133 tally the classification results of communications between multiple users included in communication history information such as chat information.

[0105] The information processing system 1 determines whether there is an unrated user (step S104). For example, the parameter estimation unit 133 determines whether there is a user whose relationship with another user has not been estimated. If there is an unrated user (step S104: Yes), the information processing system 1 returns to step S102 and performs the process.

[0106] If there are no unrated users (step S104: No), the information processing system 1 updates the relationship network (step S105). For example, the network update unit 134 updates the relationship network information based on the estimation result by the parameter estimation unit 133.

[0107] The information processing system 1 displays the updated relationship network (step S106). For example, the output unit 135 displays the updated relationship network by transmitting the relationship network to the output device 20 and displaying the relationship network on the output device 20.

[0108] [Effect] As described above, in the information processing device 100 of this embodiment, the input data acquisition unit 131, which is an example of an acquisition unit, acquires communication history information indicating the status of communication between multiple people. Furthermore, the parameter estimation unit 133, which is an example of an estimation unit, estimates relationships between the multiple people using the communication history information acquired by the acquisition unit. The network update unit 134, which is an example of an update unit, updates relationship network information indicating the relationships between the multiple people using the relationships between the multiple people estimated by the estimation unit.

[0109] In this way, the information processing device 100 uses communication history information that indicates the communication status between multiple people to estimate the relationships between multiple people and update the relationship network information that indicates the relationships between multiple people, thereby making it possible to construct relationship network information that appropriately indicates the relationships between multiple people according to the communication status of each person. Thus, the information processing device 100 can appropriately grasp the relationships between multiple people.

[0110] [Program] A program written in a computer-executable language may be created to execute the processes performed by the information processing device 100 according to the above embodiment. In one embodiment, the information processing device 100 can be implemented by installing an information processing program that executes the above information processing as package software or online software on a desired computer. For example, by executing the above information processing program on an information processing device, the information processing device can function as the information processing device 100. Other examples of information processing devices include mobile communication terminals such as smartphones, mobile phones, and PHS (Personal Handyphone Systems), as well as slate terminals such as PDAs (Personal Digital Assistants). The functions of the information processing device 100 may also be implemented on a cloud server.

[0111] 6 is a diagram showing an example of a computer that executes an information processing program. The computer 1000 includes, for example, a memory 1010, a CPU 1020, a hard disk drive interface 1030, a disk drive interface 1040, a serial port interface 1050, a video adapter 1060, and a network interface 1070. These components are connected by a bus 1080.

[0112] The memory 1010 includes a ROM (Read Only Memory) 1011 and a RAM 1012. The ROM 1011 stores a boot program such as a BIOS (Basic Input Output System). The hard disk drive interface 1030 is connected to a hard disk drive 1031. The disk drive interface 1040 is connected to a disk drive 1041. A removable storage medium such as a magnetic disk or optical disk is inserted into the disk drive 1041. The serial port interface 1050 is connected to a mouse 1051 and a keyboard 1052, for example. The video adapter 1060 is connected to a display 1061, for example.

[0113] Here, the hard disk drive 1031 stores, for example, an OS 1091, an application program 1092, a program module 1093, and program data 1094. The various pieces of information described in the above embodiments are stored in the hard disk drive 1031 or memory 1010, for example.

[0114] The information processing program is stored in the hard disk drive 1031 as, for example, a program module 1093 in which instructions to be executed by the computer 1000 are written. Specifically, the program module 1093 in which each process executed by the information processing device 100 described in the above embodiment is written is stored in the hard disk drive 1031.

[0115] Furthermore, data used for information processing by the information processing program is stored as program data 1094, for example, in the hard disk drive 1031. Then, the CPU 1020 reads the program module 1093 and the program data 1094 stored in the hard disk drive 1031 into the RAM 1012 as necessary, and executes each of the above-described procedures.

[0116] The program module 1093 and program data 1094 related to the information processing program are not limited to being stored in the hard disk drive 1031, and may be stored in, for example, a removable storage medium and read by the CPU 1020 via the disk drive 1041. Alternatively, the program module 1093 and program data 1094 related to the information processing program may be stored in another computer connected via a network such as a LAN (Local Area Network) or a WAN (Wide Area Network), and read by the CPU 1020 via the network interface 1070.

[0117] Although the present invention has been described above as an embodiment, the present invention is not limited to the description and drawings that form part of the disclosure of the present invention. In other words, other embodiments, examples, and operational techniques that can be made by those skilled in the art based on the present invention are all included in the scope of the present invention.

[0118] REFERENCE SIGNS LIST 1 Information processing system 100 Information processing device 110 Communication unit 120 Storage unit 121 History information storage unit 122 Parameter information storage unit 123 Relationship network information storage unit 130 Control unit 131 Input data acquisition unit (acquisition unit) 132 Parameter extraction unit (classification unit) 133 Parameter estimation unit (estimation unit) 134 Network update unit (update unit) 135 Output unit 10 Input device 20 Output device 50 External service device

Claims

1. An information processing device comprising: an acquisition unit that acquires communication history information indicating the status of communication between multiple people; an estimation unit that estimates the relationships between the multiple people using the communication history information acquired by the acquisition unit; and an update unit that updates relationship network information indicating the relationships between the multiple people using the relationships between the multiple people estimated by the estimation unit.

2. The information processing device described in claim 1, characterized in that it has a classification unit that classifies the content of communication between the multiple people included in the communication history information, wherein the estimation unit estimates the relationship between the multiple people based on the classification result of the content of the communication by the classification unit, and the update unit updates the relationship network information indicating the relationship between the multiple people using the relationship between the multiple people based on the classification of the content of the communication.

3. An information processing method comprising: an acquisition step of acquiring communication history information indicating the status of communication between a plurality of people; an estimation step of estimating the relationships between the plurality of people using the communication history information acquired by the acquisition step; and an update step of updating relationship network information indicating the relationships between the plurality of people using the relationships between the plurality of people estimated by the estimation step.

4. An information processing program that causes a computer to execute the following steps: an acquisition step of acquiring communication history information indicating the status of communication between multiple people; an estimation step of estimating the relationships between the multiple people using the communication history information acquired by the acquisition step; and an update step of updating relationship network information indicating the relationships between the multiple people using the relationships between the multiple people estimated by the estimation step.

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