JP5439572B1 - Detection apparatus, detection method, and detection program - Google Patents

Abstract

An object of the present invention is to identify a plurality of users who share future actions.
A detection apparatus 100 according to the present application acquires information on a user stored in an SNS server 60 that provides a social network service to a user from the SNS server. The detection apparatus 100 according to the present application has a predetermined familiarity with the reference user based on the user information stored in the SNS server 60, and the reference user and the predetermined period or more. Detect target users who have not met.
[Selection] Figure 1

Description

  The present invention relates to a detection device and the like.

  A technique for predicting a user's future behavior based on the user's past location information, information input in a schedule, or the like is disclosed (Patent Documents 1, 2, etc.). If the user's future behavior can be predicted, the information provider can provide useful information for the user by focusing on spots, products, services, etc. that are likely to be visited by the user. I can do it. In addition, if information useful for the user can be provided in this manner, the user's willingness to purchase can be promoted, which is also beneficial for the service providing side.

JP 2001-134706 A JP 2011-198292 A

  Here, if it is possible to predict the behavior of a plurality of users who share the behavior and notify each user of useful information from the predicted behavior, it is possible to further stimulate the user's willingness to purchase. However, in the above-described conventional technology, there is a problem that it is difficult to specify a plurality of users who will behave together in the future even if the behavior for each user can be predicted.

  For example, it is conceivable that future users are predicted for each user, and users who are predicted to perform similar actions are simply specified as users who perform actions together. However, even if the relationship is not good, it may happen to take similar actions, and if you provide information as a group of multiple users who do not get along well like this, it may make the user feel uncomfortable. is there.

  The disclosed technique has been made in view of the above, and an object thereof is to provide a detection device, a detection method, and a detection program that can detect a plurality of users who will behave together in the future.

  The detection device according to the present application is based on an acquisition unit that acquires, from an SNS server, user information stored in an SNS server that provides a social network service to the user, and a user information acquired by the acquisition unit. And detecting means for detecting a second user who has a predetermined familiarity with the first user and has not met with the first user for a predetermined period of time. .

  According to the detection device, the detection method, and the detection program according to the present application, there is an effect that it is possible to detect a plurality of users who will behave together in the future.

FIG. 1 is a diagram illustrating a configuration of a system according to the present embodiment. FIG. 2 is a functional block diagram illustrating the configuration of the detection apparatus according to the present embodiment. FIG. 3 is a diagram (1) illustrating an example of a data structure of user information. FIG. 4 is a diagram (2) illustrating an example of a data structure of user information. FIG. 5 is a diagram (3) illustrating an example of the data structure of the user information. FIG. 6A is a diagram illustrating an example of a data structure of template information. FIG. 6B is a diagram for explaining an example of processing of the output unit. FIG. 7 is a diagram (1) illustrating a screen example of the user terminal. FIG. 8A is a diagram (2) illustrating a screen example of the user terminal. FIG. 8B is a diagram (3) illustrating a screen example of the user terminal. FIG. 8C is a diagram (4) illustrating a screen example of the user terminal. FIG. 8D is a diagram (5) illustrating a screen example of the user terminal. FIG. 9 is a flowchart illustrating the processing procedure of the detection apparatus according to the present embodiment.

  Hereinafter, embodiments of a detection device, a detection method, and a detection program disclosed in the present application will be described in detail with reference to the drawings. Note that the present invention is not limited to the embodiments.

  A system according to the present embodiment will be described. FIG. 1 is a diagram illustrating a configuration of a system according to the present embodiment. As shown in FIG. 1, this system includes user terminals 10a, 10b, and 10c, an SNS (Social Networking Service) server 60, and a detection device 100. Here, user terminals 10a to 10c are shown as an example, but the present system may include other user terminals. Hereinafter, the user terminals 10a to 10c are collectively referred to as the user terminal 10 as appropriate. The user terminal 10, the SNS server 60, and the detection device 100 are connected to each other via the network 50. The owners of the user terminals 10a, 10b, and 10c are user A, user B, and user C, respectively.

  The user terminal 10 is a terminal device used by a user. For example, the user terminal 10 corresponds to a mobile terminal, a tablet terminal, a smartphone, or the like. The user uses the user terminal 10 to log in to the SNS server 60, publishes various types of information, and refers to information published by other users. Further, the user uses the SNS server 60 to exchange messages with other users. In addition, users can refer to photos and comments published by other users, and if they like such photos and comments, they can press the “Like” button to indicate their intention. .

  The SNS server 60 is a device that provides a social network service to the user terminal 10. For example, the SNS server 60 has a function of publishing a user's profile, photo, comment, article, etc., a function of exchanging messages between users, a function of limiting the disclosure range according to a user's request, and the like.

  The SNS server 60 provides a friend function. By using this friend function, each user who has a friend relationship can display the information posted by users registered as friends in his news field, chat, share photos, etc. You can enjoy simple communication.

  The detection apparatus 100 acquires user information accumulated in the SNS server 60 from the SNS server 60, and has a predetermined familiarity with a reference user based on the acquired user information. In addition, the apparatus detects a user who has not met with a reference user for a predetermined period of time. In the following description, a reference user is appropriately described as a reference user. In addition, a user who has a predetermined familiarity with the reference user and has not met with the reference user for a predetermined period of time is appropriately described as a target user.

  The target user detected by the detection apparatus 100 can be said to be a user who has not met directly recently, despite being intimate with the reference user. Therefore, there is a high possibility that the reference user and the target user meet directly as long as there is an opportunity to meet. After detecting the target user, the detection device 100 generates a future schedule based on the common hobbies and preferences of the reference user and the target user, and the user terminal 10 and the target usage of the reference user The user terminal 10 is notified.

  Here, as an example, the reference user is “user A” and the target user is “user B”. Further, the user terminal operated by the user A is defined as a user terminal 10a, and the user terminal operated by the user B is defined as a user terminal 10b. Further, a common hobby preference between the user A and the user B is “beer”. In this case, the detection apparatus 100 causes the user terminal 10a of the user A to display the future schedule “user B and lunch beer”. Moreover, the detection apparatus 100 displays a future schedule “user A and lunch beer” on the user terminal 10b of the user B. For example, the user A and the user B may go out for lunch beer triggered by the future schedule displayed by the detection device 100.

  Next, the configuration of the detection apparatus 100 will be described. FIG. 2 is a functional block diagram illustrating the configuration of the detection apparatus according to the present embodiment. As illustrated in FIG. 2, the detection apparatus 100 includes a communication unit 110, an input unit 120, a display unit 130, a storage unit 140, and a control unit 150.

  The communication unit 110 is a processing unit that performs data communication between the user terminal 10 and the SNS server 60. The control unit 150 described later exchanges information between the user terminal 10 and the SNS server 60 via the communication unit 110. The communication unit 110 corresponds to, for example, a communication device or a communication card.

  The input unit 120 is an input device that inputs various types of information to the detection device 100. For example, the input unit 120 corresponds to a keyboard, a mouse, a touch panel, or the like.

  The display unit 130 is a display device that displays various types of information output from the control unit 150. For example, the display unit 130 corresponds to a display, a touch panel, or the like.

  The storage unit 140 includes user information 141, template information 142, and the like. The storage unit 140 corresponds to a semiconductor memory device such as a random access memory (RAM), a read only memory (ROM), or a flash memory, or a storage device such as a hard disk or an optical disk.

  The user information 141 is user information accumulated in the SNS server 60 and is acquired by the acquisition unit 151 described later. The user information 141 includes a table 141a, a table 141b, and a table 141c. 3, 4, and 5 are diagrams illustrating an example of a data structure of user information.

  The table 141a shown in FIG. 3 will be described. The table 141a holds the user ID, name, address, mail address, and affiliation in association with each other. For example, “Mr. A” of the user ID “U101” has the address “Tokyo BB Ward XX”, the mail address “XXXXX”, and the affiliation “company A”.

  The table 141b shown in FIG. 4 will be described. The table 141b includes information defining user friendships. The friend ID indicates a user ID of a user who has a friend relationship with the user on the SNS server 60. For example, as shown in the first row of FIG. 4, the user ID of each user who has a friendship with the user ID “U101” is “..., U201, U202, U203,. , ... "

  The table 141c shown in FIG. 5 will be described. The table 141c stores an article ID, a posting date, a posted article, a comment on the posted article, position information, and photo information in association with each other for each user ID. The article ID is information that uniquely identifies an article. The posting date indicates the date when the article was posted. The posted article corresponds to the posted article. The comment on the posted article corresponds to the content of the comment made by another user on the article posted by the user. In addition, the comment on the posted article is associated with the user ID that made the comment. The position information indicates the position of the user at the time of posting the article. Photo information is information about a photo posted by a user together with an article. Note that the user information 141 illustrated in FIGS. 3 to 5 may include other information.

  The template information 142 includes template information for generating a future schedule. FIG. 6A is a diagram illustrating an example of a data structure of template information. As illustrated in FIG. 6, the template information 142 holds a template ID and a template content in association with each other. The template ID is information that uniquely identifies the template. The template content corresponds to the template content. The template content “[]” corresponds to the variable area, and when a future schedule is generated, the corresponding wording is appropriately input.

  The control unit 150 includes an acquisition unit 151, a detection unit 152, and an output unit 153. The control unit 150 corresponds to an integrated device such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA). Moreover, the control part 150 respond | corresponds to electronic circuits, such as CPU and MPU (Micro Processing Unit), for example.

  The acquisition unit 151 is a processing unit that acquires user information stored in the SNS server 60 from the SNS server 60. The acquisition unit 151 stores the user information acquired from the SNS server 60 in the storage unit 140 as user information 141.

  The detection unit 152 is a processing unit that detects a target user who has a predetermined familiarity with the reference user and has not met with the reference user for a predetermined period based on the user information 141. is there. Hereinafter, a process in which the detection unit 152 determines a user who has a predetermined familiarity and a process in which a user who has not met with a reference user for a predetermined period of time will be described in order.

  An example of processing in which the detection unit 152 detects a user who has a predetermined familiarity with the reference user will be described. Here, the reference user is described as the user A having the user ID “U101”. The detecting unit 152 refers to the table 141c of the user information 141 and refers to the comment column for the posted article with the user ID “U101”, thereby making a comment on the posted article created by the user A. And the number of times the user clicks “Like” is counted for each user. Then, the detection unit 152 detects a user who has a predetermined number of comments or the number of times the user has pressed “Like” as a user having a predetermined familiarity with the reference user. To do.

  Further, the detecting unit 152 refers to the table 141b of the user information 141 and detects a user who has a friendship with the reference user as a user who has a predetermined familiarity with the reference user. good.

  An example of processing in which the detection unit 152 determines a user who has not met the reference user for a predetermined period or more will be described. Here, the reference user is described as the user A having the user ID “U101”. The detection unit 152 refers to the table 141c of the user information 141, and matches the combination of the posting date and position information of the user A with the combination of the posting date and position information of another user, and the user A And whether other users meet directly.

  For example, the use of the user ID “U102” for the set of the post date “October 1, 2012 12:30:30” and the position information “aabbcc” of the user A of the user ID “U101” The combination of the posting date of the person B “October 1, 2012 12:30:30” and the position information “aabbcc” is the same. For this reason, the detection unit 152 determines that the user A and the user B met directly on “October 1, 2012, 12:30:30”. The detection unit 152 may provide a margin less than a predetermined value and perform matching between a combination of the posting date and position information of the user A and a combination of another user's posting date and position information. good.

  After executing the matching process, the detection unit 152 detects a user who has not met with the user A for a predetermined period since the last time.

  The detection unit 152 executes the above processing to detect a target user who has a predetermined familiarity with the reference user and has not met the reference user for a predetermined period of time. For example, a user who has a predetermined familiarity with a reference user is “user B, user C, user D”, and a user who has not met the reference user for a predetermined period of time is referred to as “user. B, user E, user F ”, the detection unit 152 detects“ user B ”as the target user. The detection unit 152 outputs information on the reference user and the target user to the output unit 153.

  The output unit 153 generates a future schedule based on the hobby preference common to the reference user and the target user and the template information 142. The output unit 153 notifies the SNS server 60 of the generated future schedule, and displays it on the user terminal 10 of the reference user and the target user.

  The output unit 153 identifies a common hobby preference of the reference user and the target user. Here, as an example, a hobby preference is a product or service. The output unit 153 refers to the table 141c of the user information 141 and matches the content of the posted article corresponding to the user ID of the reference user with the content of the posted article corresponding to the user ID of the target user. Detects product names and service names that appear in common in each posted article. The output unit 153 identifies the detected product name or service name as a common hobby preference for the reference user and the target user.

  A process of generating a schedule after the output unit 153 specifies a product name or a service name that becomes a common hobby preference will be described. The output unit acquires a template corresponding to the common hobby preference from the template information 142.

  For example, when the common hobby preference relates to a pub, a restaurant, karaoke, a sightseeing spot, etc., the output unit 153 acquires a template with the template ID “C101” and generates a future schedule.

  For example, when the common hobby preference relates to a television program or the like, the output unit 153 acquires a template with the template ID “C102” and generates a future schedule.

  For example, when the common hobby preference is related to a movie or the like, the output unit 153 acquires a template with the template ID “C103” and generates a future schedule.

  Here, as an example, the reference user is “user A”, the target user is “user B”, the common hobby preference is “izakaya”, and the schedule to be displayed on the user terminal 10 of user A is as follows: A case where the output unit 153 generates will be described.

  FIG. 6B is a diagram for explaining an example of processing of the output unit. As illustrated in FIG. 6B, since the common hobby preference is “izakaya”, the output unit 153 selects the template with the template ID “C101”. Such a template has variable regions 20a, 20b, 20c, and 20d. The output unit 153 sets “user B” in the variable areas 20a and 20c.

  The output unit 153 determines a word to be input to the variable area 20b. For example, the output unit 153 extracts a spot related to a tavern from hot spots, and sets the extracted wording in the variable region 20b. For example, the output unit 153 sets “Izakaya XX”. Information about hot spots may be stored in advance in the storage unit 140 or the like, or may be acquired from the network.

  The output unit 153 determines a word to be input to the variable area 20d. For example, the output unit 153 extracts an event related to a tavern from a predetermined event, and sets the extracted wording in the variable region 20d. For example, the output unit 153 sets “a drinking party”. Information about a predetermined event may be stored in advance in the storage unit 140 or the like, or may be acquired from the network.

  By performing the above processing, the output unit 153 causes the schedule to be displayed on the user terminal 10 of the user A “To the user B and the tavern XX. I was able to speak a lot after a long time! “Drinking party” is generated. Similarly, the output unit 153 displays a schedule to be displayed on the user terminal 10 of the user B “To user A and the tavern XX. I was able to talk a lot after a long time! Is generated.

  After generating the future schedule, the output unit 153 attaches advertisement information related to the product or service included in the future schedule to the schedule. Advertisement information related to a product or service may be stored in advance in the storage unit 140 or the like, or may be acquired from the network.

  The output unit 153 transmits the reference user information, the future schedule information of the reference user, the target user information, the future schedule information of the target user, and the advertisement information to the SNS server 60.

  When the user A operates the user terminal 10a to log in to the SNS server 60 and performs an operation for displaying the future timeline, the future schedule generated by the output unit 153 is displayed. 7 and 8A to 8D are diagrams illustrating screen examples of the user terminal. As shown in FIG. 7, advertisement information is displayed together with a future schedule. When the user A presses the like button 30, the future schedule is added to the timeline of the SNS server 60. Note that the output unit 153 may display the advertisement information in any way. For example, the advertisement information may be displayed as an overlay, may be displayed as an article, may be displayed by an advertisement application included in the content, or may be displayed by a web advertisement.

  Further, as shown in FIG. 8A, when the user A presses the like button 31, information indicating that the user A has pressed the like is displayed on the user terminal 10b of the user B of the target user. Is displayed. As shown in FIG. 8B, the future that user A does not want to realize may be changed by himself. Further, as shown in FIG. 8C, the output unit 153 causes the user terminal 10 to display information for asking whether or not the future schedule has actually been executed. Information to that effect may be sent to the timeline. Moreover, as shown in FIG. 8D, other friends can easily participate in the activity by flowing in the timeline.

  Next, an example of a processing procedure of the detection apparatus 100 according to the present embodiment will be described. FIG. 9 is a flowchart illustrating the processing procedure of the detection apparatus according to the present embodiment. As illustrated in FIG. 9, the detection apparatus 100 acquires user information accumulated in the SNS server 60 and registers it in the storage unit 140 (step S <b> 101).

  The detection apparatus 100 selects a reference user (step S102). The detection apparatus 100 detects a target user who has a predetermined familiarity with the reference user and has not met the reference user for a predetermined period of time (step S103).

  The detection apparatus 100 compares the reference user information and the target user information to determine a common hobby preference (step S104). The detection apparatus 100 selects a standard product or service (step S105).

  The detection apparatus 100 filters a standard product or service with a common hobby preference (step S106). The detection apparatus 100 generates a future schedule based on the filtering result (step S107). The detection apparatus 100 publishes the future schedule together with the advertisement (step S108).

  Next, the effect of the detection apparatus 100 according to the present embodiment will be described. The detection apparatus 100 according to the present embodiment acquires user information accumulated in the SNS server 60. The detection apparatus 100 detects a target user who has a predetermined familiarity with the reference user and has not met with the reference user for a predetermined period or more based on the user information. For this reason, according to the detection apparatus 100, it is possible to detect a target user who is highly likely to behave together with the reference user.

  In addition, since the detection apparatus 100 extracts products or services that are common between the reference user information and the target user information, the reference user and the target user are actually used based on the extracted information. Propose future schedules that make it easier to take action.

  In addition, since the detection apparatus 100 outputs advertisement information related to a common product or service between the reference user information and the target user information in association with each other, the advertising effect on the reference user and the target user is output. Can stimulate purchase incentives.

  By the way, the embodiment of the detection apparatus 100 described above is an example. Hereinafter, other embodiments of the detection apparatus 100 will be described.

  For example, the detection unit 152 detects a target user who has a predetermined familiarity with the reference user and has not met the reference user for a predetermined period based on the user information 141. However, the target user may be detected using other conditions.

  Other processing of the detection unit 152 will be described. The detection unit 152 detects, as a target user, a user whose distance from the reference user is less than the predetermined distance after a period in which the distance from the reference user is equal to or greater than the predetermined distance has elapsed.

  For example, the detection unit 152 refers to the table 141c of the user information 141, compares the set of the reference user's posting date and position information with the posting date and position information of other users who are friends, A user whose distance from the reference user is less than the predetermined distance is detected as a target user after a period in which the distance from the user is equal to or greater than the predetermined distance elapses.

  In this way, after a period in which the distance from the reference user is equal to or greater than the predetermined distance has elapsed, a user whose distance from the reference user is less than the predetermined distance is expected to meet the reference user after a long time. It is highly possible that For this reason, it is considered that the reference user and the target user meet directly if given a chance. Therefore, it is possible to detect each user who will behave together in the future.

  For example, even when the user A and the user B are in a friendship relationship, the user A's action range is Osaka, and the user B's action range is Tokyo. Under such conditions, when user A comes out of Tokyo for a long time due to a business trip or the like, if the future schedule is disclosed to the user terminals 10 of user A and user B, the user A The user A and the user B can be met, and at the same time, the advertisement of goods and services can be effectively performed.

  By the way, the detection unit 152 may further narrow down the target users by further using the affiliation of the reference user and the affiliation of the target user. For example, users who belong to the same company are likely to meet frequently at the company and may not want to meet again in private. Even if a future schedule is disclosed to such a user, the possibility of meeting according to the schedule is low.

  For this reason, the detection unit 152 targets a user who has a predetermined familiarity with the reference user, has not met the reference user for a predetermined period of time, and whose affiliation is different from that of the reference user. You may detect as a user.

  In addition, when detecting the target user of the reference user, the detection unit 152 detects a target user who is likely to meet the reference user based on not only the familiarity but also the daily action range. Also good. For example, when the average position of the position information of the target user is included in a predetermined range from the average position of the position information of the reference user based on the table 141c, the detection unit 152 It is determined that there is a high possibility of meeting the reference user.

  The detection unit 152 may further select the habitual action range and date / time of the reference user and the target user. For example, the reference user and the target user have overlapping action ranges from Monday to Friday, but may have different action ranges on Saturday and Sunday. In this case, in consideration of the action range from Monday to Friday, a future schedule that can be executed in the action range is generated, and a proposal to perform the schedule on Friday is made to the reference user and the target user. Also good.

  When the action range between the reference user and the target user is within the predetermined range, the output unit 153 generates a future schedule related to the spots within the predetermined range, and generates the reference user and the target user. It may be disclosed to users.

  In addition, the output unit 153 allows other users to post comments and the like for the future schedule proposed to the reference user and the target user, and other users can also participate in the schedule. It is also good.

  As described above, some of the embodiments of the present application have been described in detail with reference to the drawings. However, these are merely examples, and various modifications, including the aspects described in the disclosure section of the invention, based on the knowledge of those skilled in the art It is possible to implement the present invention in other forms with improvements.

10a, 10b, 10c User terminal 50 Network 60 SNS server 100 Detection device 110 Communication unit 120 Input unit 130 Display unit 140 Storage unit 150 Control unit

Claims (6)

Obtaining means for obtaining from the SNS server information on the user stored in the SNS server that provides the social network service to the user;
Based on the information of the user acquired by the acquisition means, the first user has a predetermined familiarity and has not met the first user for a predetermined period of time. And a detecting means for detecting two users.   Based on the user information acquired by the acquisition means, a common product or service is extracted between the first user information and the second user information, and the extracted common information The detection apparatus according to claim 1, further comprising output means for outputting information on goods or services.   The detection apparatus according to claim 2, wherein the output unit outputs advertisement information related to the common product or service in association with the information of the common product or service.   The detection means, based on the information of the user acquired by the acquisition means, the first user after a period in which the distance to the first user is a predetermined distance or more has elapsed. The detection apparatus according to claim 1, further detecting a user whose distance to the user is less than a predetermined distance as the second user. A detection method performed by a detection device,
An acquisition step of acquiring, from the SNS server, user information stored in an SNS server that provides social network services to users;
Based on the information of the user acquired in the acquisition step, the first user has a predetermined familiarity and has not met the first user for a predetermined period or more. And a detection step of detecting the user of 2. An acquisition procedure for acquiring, from the SNS server, user information stored in an SNS server that provides a social network service to the user;
Based on the information on the user acquired by the acquisition procedure, the first user has a predetermined familiarity and has not met the first user for a predetermined period or more. A detection program for causing a computer to execute a detection procedure for detecting a user of (2).

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