JP2019079418A - Estimation apparatus, estimation method, and estimation program - Google Patents

Abstract

To properly estimate context of a user.SOLUTION: An estimation apparatus according to the present application includes an acquisition unit and an estimation unit. The acquisition unit acquires common action information which indicates that first user and second user has taken common action, and first context information indicating context of the first user on a first date and time. The estimation unit estimates context of the second user on a second date and time, which is different from the first date and time, on the basis of the common action information and the first context information acquired by the acquisition unit.SELECTED DRAWING: Figure 5

Description

  The present invention relates to an estimation apparatus, an estimation method, and an estimation program.

  Conventionally, there is provided a technology that uses information of another user as information of one user. For example, when a user accesses an application in a non-smart space or in a different smart space, a technique is known that also acquires an environment context that is deficient by the user.

JP-A-2017-503371

  However, the above-mentioned prior art can not necessarily estimate the context of the user appropriately. For example, in the above-mentioned prior art, it may be difficult to appropriately estimate the context of the user, since the information of the other user is only acquired when the information is insufficient. For example, when information is not acquired for another user at a certain time, it is difficult to appropriately estimate the context of the user at that time.

  This application is made in view of the above, and an object of the present application is to provide an estimation device, an estimation method, and an estimation program which estimate a user's context appropriately.

  The estimation apparatus according to the present application includes common action information indicating that the first user and the second user have performed common actions that are common actions, and first context information indicating the context of the first user at a first date and time And estimating the context of the second user at a second date and time different from the first date and time, based on the common behavior information and the first context information acquired by the acquisition unit and the acquisition unit for acquiring the And an estimation unit.

  According to an aspect of the embodiment, an effect is obtained that the context of the user can be appropriately estimated.

FIG. 1 is a diagram illustrating an example of estimation processing according to the embodiment. FIG. 2 is a diagram showing an example of estimation processing according to the embodiment. FIG. 3 is a diagram showing an example of estimation processing according to the embodiment. FIG. 4 is a diagram showing an example of the configuration of the estimation system according to the embodiment. FIG. 5 is a diagram showing an example of the configuration of the estimation apparatus according to the embodiment. FIG. 6 is a diagram illustrating an example of the user information storage unit according to the embodiment. FIG. 7 is a diagram illustrating an example of the context information storage unit according to the embodiment. FIG. 8 is a diagram illustrating an example of the common behavior information storage unit according to the embodiment. FIG. 9 is a diagram illustrating an example of the estimated information storage unit according to the embodiment. FIG. 10 is a flowchart illustrating an example of estimation processing according to the embodiment. FIG. 11 is a diagram illustrating an example of estimation processing according to the embodiment. FIG. 12 is a hardware configuration diagram showing an example of a computer for realizing the function of the estimation device.

  Hereinafter, an estimation apparatus, an estimation method, and a form for implementing an estimation program (hereinafter, referred to as “embodiment”) according to the present application will be described in detail with reference to the drawings. Note that the estimation apparatus, estimation method, and estimation program according to the present application are not limited by this embodiment. Moreover, the same code | symbol is attached | subjected to the same site | part in the following each embodiment, and the overlapping description is abbreviate | omitted.

(Embodiment)
[1. Estimation process]
An example of the estimation process according to the embodiment will be described using FIGS. 1 to 3. 1 to 3 are diagrams showing an example of estimation processing according to the embodiment. In the example of FIG. 1, using the information (common action information) indicating that the estimation apparatus 100 has performed a common action with the user U1 as the first user and the user U2 as the second user, position information ( Hereinafter, a case where the position of the user U2 whose status is simply referred to as "position" is not estimated will be shown. Further, in the example of FIG. 1, the estimation apparatus 100 estimates the position of the user U2 at a second date and time different from the first date and time based on the context information indicating the position of the user U1 at the first date and time. That is, the first user here corresponds to the user whose context information is used, and the second user corresponds to the user whose context is estimated. The details of the common action and the context will be described later. Note that the date and time referred to here may be a certain time point (hour, minute, second), or may include a certain period (for example, a period in minutes).

[Configuration of estimation system]
First, prior to the description of FIGS. 1 to 3, the configuration of the estimation system 1 will be described using FIG. 4. FIG. 4 is a diagram showing an example of the configuration of the estimation system according to the embodiment. As shown in FIG. 4, the estimation system 1 includes a terminal device 10-1, a terminal device 10-2, a terminal device 10-3, and an estimation device 100. The terminal device 10-1, the terminal device 10-2, the terminal device 10-3, and the estimation device 100 are communicably connected by wire or wireless via a predetermined network N.

  Hereinafter, the terminal devices 10-1 to 10-3 will be referred to as the terminal device 10 when the description is made without particular distinction. Although three terminal devices 10-1 to 10-3 are illustrated in the estimation system 1 shown in FIG. 4, four or more terminal devices 10 may be included in the estimation system 1. For example, the estimation system 1 may include the terminal device 10 corresponding to each user, and may include one million terminal devices 10 when the number of users is one million. Further, the estimation system 1 illustrated in FIG. 4 may include a plurality of estimation devices 100.

  The terminal device 10 is an information processing device used by a user. The terminal device 10 is realized by, for example, a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like. In the example shown in FIG. 1, the case where the terminal device 10 is a smart phone which a user utilizes is shown. In the following, the terminal device 10 may be described as a user. That is, the user can be read as the terminal device 10 below.

  For example, the terminal device 10-1 corresponds to the terminal device 10 used by the user U1 illustrated in FIG. As described above, when “user U * (* is any numerical value)” is described, it indicates that the user is a user identified by the user ID “U *”. For example, when "user U1" is described, the user is a user identified by user ID "U1". For example, the terminal devices 10-2 and 10-3 correspond to the terminal devices 10 used by the users U2 and U3 shown in FIG. Moreover, below, the terminal device 10 which a user utilizes, and the user may be mutually read. For example, when it describes as "the user U1", it may be read as "the terminal device 10-1" which is the terminal device 10 which the user U1 utilizes. When described as "terminal device 10-1," it may be read as "user U1" which is a user who uses the terminal device 10-1. In the following, in order to simplify the description, a case where the terminal device 10 used by the user can be specified by the user ID will be described as an example.

  In addition, the terminal device 10 may detect various sensor information by using various sensors such as a GPS (Global Positioning System) sensor. The terminal device 10 also has a function of an acceleration sensor, and detects and acquires acceleration information (sensor information) in the movement of the user. In addition, the terminal device 10 may have various functions such as a temperature sensor and an air pressure sensor, and may detect and acquire environment information on which the user is placed, such as temperature and air pressure. Further, the terminal device 10 may have various functions such as a heart rate sensor, and may be capable of detecting and acquiring biometric information of the user. For example, the user using the terminal device 10 may be able to acquire the user's own context information from the terminal device 10 by wearing a wearable device capable of communicating with the terminal device 10. For example, the user using the terminal device 10 may be able to obtain information on the user's own heartbeat (pulse) by wearing the wristband type wearable device capable of communicating with the terminal device 10 .

  Further, the terminal device 10 performs near-field communication with another terminal device 10 by near field communication technology. For example, the terminal device 10 has a function of performing proximity communication with another terminal device 10 by using various conventional techniques related to NFC (Near Field Communication) as appropriate. For example, the terminal device 10 may perform proximity communication with another terminal device 10 by appropriately using various conventional wireless communication technologies such as Bluetooth (registered trademark) and WiFi (registered trademark) (Wireless Fidelity). . That is, the terminal device 10 may perform proximity communication with another terminal device 10 using any function as long as proximity communication with the other terminal device 10, that is, so-called passing communication, is possible.

  Here, the proximity may be a range in which wireless communication is possible, or may be a range within a predetermined threshold. For example, proximity may be a specific distance such as 1 meter or 10 meters. Furthermore, in the following, it is assumed that the terminal device 10 performs near-field communication with another terminal device 10 by Bluetooth (registered trademark).

  Further, the terminal device 10 collects information on the context of the user (hereinafter, also referred to as “context information”), and transmits the information to the estimation device 100. For example, the terminal device 10 may transmit context information to the estimation device 100 at any time (in real time) when detecting (acquiring) context information of the user, or at predetermined timing (for example, every hour or one) Context information may be transmitted to the estimation apparatus 100 on a daily basis.

  The context herein may be a concept including an environment in which the user is placed. For example, the terminal device 10 collects user's position information and transmits it to the estimation device 100. For example, the terminal device 10 collects various types of behavior information of the user on the terminal device 10 and transmits the information to the estimation device 100. For example, the terminal device 10 collects information on the content browsed by the user on the terminal device 10 and transmits the information to the estimation device 100.

  For example, the context referred to here may be a concept including the user or the situation of the terminal device 10 used by the user, or the user's various situations based on the user or the environment (background) of the terminal device 10. Further, the context information includes the current position of the user, the current time, the physical environment in which the user is placed, the social environment in which the user is placed, the user's behavior, the user's exercise state, the content of the content provided to the user, the user Contains various information such as the content of the content to which the user has responded, the attribute of the user, and the emotion of the user. For example, the context information includes information based on various actions of the user. Also, for example, the context information includes the position of the user, the moving means of the user, the state of the user, and the like. Also, for example, the context information includes the communication state of the terminal device 10 used by the user, information to be displayed, and the like. The above is an example, and the context information is not limited to the above, and various information may be included.

  The estimation apparatus 100 is based on common action information indicating that the first user and the second user have performed common actions that are common actions, and first context information indicating the context of the first user at the first date and time. Is an information processing apparatus that estimates the context of the second user. For example, the estimation apparatus 100 determines a second date and time at a second date and time that is different from the first date and time based on common behavior information between the first user and the second user and the first context information on the first user at the first date and time. Estimate the context of the user.

  For example, the estimation apparatus 100 may provide various services using information on the estimated context of the user. For example, the estimation apparatus 100 may perform a service of providing information on the estimated context of the user to another information processing apparatus. Also, for example, the estimation apparatus 100 may perform a service (content providing service) for providing content to the user. The estimation device 100 may distribute the content displayed on the terminal device 10 in response to a request from the terminal device 10. For example, the estimation apparatus 100 may provide the content according to the context of the user in response to a request from the terminal device 10 used by the user. Further, in the estimation system 1, the estimation device 100 may provide various services such as a search service and an electronic commerce service.

  For example, the estimation apparatus 100 provides the terminal device 10 with information of a product or service (hereinafter also referred to as a “product”), or delivers the product to the user according to the information indicating the purchase intention from the user. , Etc. may be provided. Also, for example, the estimation apparatus 100 may provide a search service for providing the terminal device 10 with a search result for a query (search query) acquired from the terminal device 10.

[1-1. When the first user is one person]
From here, the case where the position of the user U2 is estimated will be described as an example using FIG. Map information MP11 (hereinafter, also simply referred to as "map MP11") shown in FIG. 1 schematically indicates the positions of the user U1, the user U2, and the like. Map MP11-1 shown in FIG. 1 is for showing road information RD11, and map MP11-1 is the same area as map MP11. Moreover, in the following, the map MP11-1 will be described as the map MP11 when the description is made without particular distinction. Further, the position LC11 and the positions LC1 to LC6 illustrated in the map MP11 may be information indicating specific latitude and longitude. In the example of FIGS. 1 to 3, the common action is to be located at a position where each user approaches, and the terminal device 10 used by each user may be located at a proximity position by performing proximity communication. Indicates the identified case.

  First, the estimation apparatus 100 (see FIG. 5) acquires context information of the user U1 at the date and time dt11 (step S11). In the example of FIG. 1, the terminal device 10-1 used by the user U1 has a position LC11 at which the position of the terminal device 10-1 (user U1) at the date and time dt11 is the position LC11 by the function of detecting predetermined position information such as GPS. Get context information to indicate that. For example, when the terminal device 10-1 transmits context information indicating that the position of the user U1 is the position LC11 to the estimation device 100, the estimation device 100 acquires context information of the user U1 at the date dt11.

  Then, the terminal device 10-1 performs near-field communication with the terminal device 10-2 used by the user U2 at the date and time dt12 (step S12). For example, the terminal device 10-1 and the terminal device 10-2 perform passing communication at the date and time dt12 by a function such as Bluetooth (registered trademark). That is, the terminal device 10-1 and the terminal device 10-2 detect information indicating that the user U1 is located near the user U2 at the date and time dt12. For example, the terminal device 10-1 and the terminal device 10-2 collect context information indicating that the user U1 has passed the user U2 at the date and time dt12, and transmit the context information to the estimation device 100. Note that only one of the terminal device 10-1 and the terminal device 10-2 may transmit context information indicating that the user U1 has passed the user U2 to the estimation device 100 at the date dt12. Thereby, the estimation apparatus 100 acquires common action information (context information) indicating that the user U1 and the user U2 approach each other at the date and time dt12 (step S13). For example, the estimation apparatus 100 acquires common action information indicating that the user U1 and the user U2 have passed each other at the date dt12.

  Then, the estimation apparatus 100 estimates the position of the user U2 at the date dt12 based on the position LC11 of the user U1 at the date dt11 and the common action information indicating that the user U1 and the user U2 approach at the date dt12. (Step S14). For example, the estimation apparatus 100 performs proximity communication with the user U1 based on the position LC11 of the user U1 at the date dt11 and the common action information indicating that the user U1 and the user U2 approach at the date dt12. Estimate the position.

  In the example of FIG. 1, the estimation apparatus 100 determines the position of the user U2 at the date dt12 based on the time between the date dt11 and the date dt12 (hereinafter, also referred to as “elapsed time”) and the walking speed of the user U1. presume. For example, the estimation apparatus 100 estimates the movable range of the user U1 from the position LC11 in the elapsed time based on the walking speed WS1 of the user U1 as shown in the user information storage unit 121 (see FIG. 6). If the estimation device 100 does not have the walking speed corresponding to the user U1, the user U1 moves from the position LC11 in the elapsed time based on the user attribute to which the user U1 belongs, that is, the average walking speed of a 20's male. The possible range may be estimated.

  For example, when the walking speed of the user U1 is “6 km / h (kilometers per hour)” and the elapsed time between the date and time dt11 and the date and time dt12 is 30 minutes, the estimation device 100 determines that the user U1 is in the elapsed time It is estimated that it can move by about "3 km (= 6 * 0.5)". In this case, the estimating apparatus 100 estimates that the user U1 and the user U2 have passed each other around a radius of 3 km centered on the position LC11.

  In the example of FIG. 1, the estimation apparatus 100 estimates that the user U1 and the user U2 pass each other at any position on the circle CR11 at the date dt12. That is, the estimation apparatus 100 estimates that the position of the user U2 at the date and time dt12 is any position on the circle CR11. Note that the circle CR11 in FIG. 1 may be an annular shape having a predetermined width (for example, 1 m, 50 m, etc.), and the estimation device 100 assumes that the user U2 is located somewhere in the annular circle CR11. It may be estimated. Note that the estimation apparatus 100 may also estimate that the position of the user U2 at the date and time dt12 is any position on the circle CR11 for the user U1.

  As described above, the estimation apparatus 100 uses the user at the date dt12 based on the position LC11 of the user U1 other than the user U2 and the common action information indicating that the user U1 and the user U2 approach each other at the date dt12. The position of U2 can be estimated. Thus, the estimation apparatus 100 appropriately estimates the position of the user by using information of another user or common behavior information with another user, even if the user has not acquired position information. be able to. Therefore, the estimation device 100 can appropriately estimate the context of the user.

[1-1-1. Use of road information]
Further, the estimation device 100 may estimate the position of the user by using road information in addition to the context information and the common action information of other users. For example, the estimation apparatus 100 may narrow down the candidates for the position of the user based on the road information.

  The estimation device 100 acquires road information (step S15). In the example of FIG. 1, road information in the map MP11 is acquired. For example, the estimation apparatus 100 acquires road information in the map MP11 from the road map information storage unit 125 (see FIG. 5). In the example of FIG. 1, the estimation device 100 acquires road information RD11 as shown in the map MP11 in FIG. Note that the estimation device 100 may acquire road information in the map MP11 from a predetermined external device. For example, the estimation device 100 may acquire road information in the map MP11 from a service providing device that provides a road map service.

  Then, the estimation apparatus 100 estimates the position of the user U2 at the date dt12 based on the circle CR11 in FIG. 1 and the road information RD11 (step S16). For example, the estimation apparatus 100 narrows down the position of the user U2 at the date dt12 from the circle CR11 based on the circle CR11 in FIG. 1 and the road information RD11. Specifically, the estimation apparatus 100 estimates a point (position) where the circle CR11 in FIG. 1 intersects with the road information RD11 as the position of the user U2 at the date dt12. In the example of FIG. 1, the estimation device 100 estimates six positions LC1 to LC6 where the circle CR11 in FIG. 1 intersects the road information RD11 as the position of the user U2 at the date dt12.

  Thus, the estimation apparatus 100 can narrow down the position of the user U2 at the date dt12 from the circle CR11 to six positions LC1 to LC6 by using the road information RD11. As described above, the estimation apparatus 100 can appropriately estimate the position of the user by using the road information in addition to the context information and the common action information of the other users. Therefore, the estimation device 100 can appropriately estimate the context of the user.

  As described above, the estimation apparatus 100 uses the user at the date dt12 based on the position LC11 of the user U1 other than the user U2 and the common action information indicating that the user U1 and the user U2 approach each other at the date dt12. The position of U2 can be estimated. Thus, the estimation apparatus 100 appropriately estimates the position of the user by using information of another user or common behavior information with another user, even if the user has not acquired position information. be able to. Therefore, the estimation device 100 can appropriately estimate the context of the user. In the example of FIG. 1, the estimation apparatus 100 can complement the position information at the date dt12 of the user U2 whose position information has not been acquired, with the information of the other user U1. As described above, the estimation apparatus 100 can supplement the context information of the user at the date and time when the context information can not be acquired.

[1-2. When the first user is two people]
In the example shown in FIG. 1, the date / time dt12 for estimating the position of the user U2 is later than the date / time dt11 for which the user U1 is located at the position LC11. The date and time of For example, the date and time when the position of the user U2 is estimated may be earlier than the date and time when the position of the user U1 is detected. Also, the number of first users is not limited to one, and may be two or more. These points will be described with reference to FIG.

  The map information MP21 (hereinafter, also simply referred to as "map MP21") shown in FIG. 2 schematically indicates the positions of the user U1, the user U2, and the like. Further, the position LC21 and the position LC31 illustrated in the map MP21 may be information indicating specific latitude and longitude.

  First, the terminal device 10-1 performs proximity communication with the terminal device 10-2 used by the user U2 at the date and time dt21 (step S21). For example, the terminal device 10-1 and the terminal device 10-2 perform passing communication at the date and time dt21 using a function such as Bluetooth (registered trademark). That is, the terminal device 10-1 and the terminal device 10-2 detect information indicating that the user U1 is located near the user U2 at the date dt21. For example, the terminal device 10-1 and the terminal device 10-2 collect context information indicating that the user U1 has passed the user U2 at the date and time dt21, and transmit the context information to the estimation device 100. Note that only one of the terminal device 10-1 and the terminal device 10-2 may transmit context information indicating that the user U1 has passed the user U2 to the estimation device 100 at the date dt21. Thereby, the estimation apparatus 100 acquires common action information (context information) indicating that the user U1 and the user U2 approach each other at the date and time dt21 (step S22). For example, the estimation apparatus 100 acquires common action information indicating that the user U1 and the user U2 have passed each other at the date and time dt21.

  Then, the estimation apparatus 100 (see FIG. 5) acquires context information of the user U1 at the date and time dt22 (step S23). In the example of FIG. 2, the terminal device 10-1 used by the user U1 has a position LC21 at which the position of the terminal device 10-1 (user U1) at the date and time dt22 is determined by the function of detecting predetermined position information such as GPS. Get context information to indicate that. For example, when the terminal device 10-1 transmits context information indicating that the position of the user U1 is the position LC21 to the estimation device 100, the estimation device 100 acquires context information of the user U1 at the date dt22.

  The estimation apparatus 100 (see FIG. 5) acquires context information of the user U3 at the date and time dt23 (step S24). In the example of FIG. 2, the terminal device 10-3 used by the user U3 has a position LC31 at which the position of the terminal device 10-3 (user U3) at the date and time dt23 is determined by the function of detecting predetermined position information such as GPS. Get context information to indicate that. For example, when the terminal device 10-3 transmits context information indicating that the position of the user U3 is the position LC31 to the estimation device 100, the estimation device 100 acquires context information of the user U3 at the date and time dt23.

  The terminal device 10-3 performs near-field communication with the terminal device 10-2 used by the user U2 at the date and time dt24 (step S25). For example, the terminal device 10-3 and the terminal device 10-2 perform passing communication at the date and time dt24 by a function such as Bluetooth (registered trademark). That is, the terminal device 10-3 and the terminal device 10-2 detect information indicating that the user U3 is located near the user U2 at the date and time dt24. For example, the terminal device 10-3 and the terminal device 10-2 collect context information indicating that the user U3 has passed the user U2 at the date and time dt24, and transmit the context information to the estimation device 100. Note that only one of the terminal device 10-3 and the terminal device 10-2 may transmit context information indicating that the user U3 has passed the user U2 to the estimation device 100 at the date dt24. Thereby, the estimation apparatus 100 acquires common action information (context information) indicating that the user U3 and the user U2 approach each other at the date and time dt24 (step S26). For example, the estimation apparatus 100 acquires common action information indicating that the user U3 and the user U2 have passed each other at the date and time dt24.

  Then, the estimation apparatus 100 estimates the position of the user U2 at the date dt21 based on the common action information indicating that the user U1 and the user U2 approach each other at the date dt21, and the position LC21 of the user U1 at the date dt22. (Step S27). For example, in the estimation apparatus 100, the user U2 performs proximity communication with the user U1 based on the common behavior information indicating that the user U1 and the user U2 approach at the date dt21 and the position LC21 of the user U1 at the date dt22. Estimate the position. For example, as in FIG. 1, the estimation apparatus 100 centers the position LC21 on the basis of the elapsed time from the date and time dt21 to the date and time dt22 and the walking speed of the user U1 and radiuses the distance that the user U1 can move in the elapsed time Estimate the circle to be taken ("the first circle").

  Further, the estimation apparatus 100 estimates the position of the user U2 at the date dt24 based on the position LC31 of the user U3 at the date dt23 and the common action information indicating that the user U3 and the user U2 approach at the date dt24. (Step S28). For example, estimation apparatus 100 performs proximity communication with user U2 based on position LC31 of user U3 at date dt23 and common action information indicating that user U3 and user U2 approach at date dt24. Estimate the position. For example, as in FIG. 1, the estimation apparatus 100 centers the position LC31 on the basis of the elapsed time from the date dt23 to the date dt24 and the walking speed of the user U3 and radiuses the distance that the user U3 can move in the elapsed time. Estimate the circle to be taken ("the second circle").

  Then, the estimation apparatus 100 determines the position of the user U2 in the first circle and the second circle based on the elapsed time between the date and time dt21 and the date and time dt24 for which the position of the user U2 is to be estimated and the date and time dt24. The position of the user U2 in is narrowed down. For example, the estimation apparatus 100 determines the position of the user U2 in the first circle or the first distance based on the distance that the user U2 can move in the elapsed time between the date dt21 and the date dt24 (hereinafter, also referred to as “moving distance”). The position of the user U2 in 2 yen is narrowed down.

  For example, the estimation apparatus 100 estimates that the position of the user U2 at the date and time dt21 is on the arc CA21 of the first circle in which the distance to any point on the circumference of the second circle is within the movement distance. Do. Note that the arc CA21 in FIG. 2 may have a predetermined width (for example, 1 m, 50 m, etc.), and it may be estimated that the user U2 is located somewhere in the arc CA21 having a width. That is, the estimation apparatus 100 estimates that the position of the user U2 at the date dt21 is a circular arc CA21 narrowed more than the first circle.

  Also, for example, in the estimation device 100, the position of the user U2 at the date and time dt24 is on the arc CA31 of the second circle in which the distance between any of the points on the circumference of the first circle is within the movement distance. Estimate. In addition, circular arc CA31 in FIG. 2 may have a predetermined width (for example, 1 m, 50 m, etc.), and it may be estimated that user U2 is located somewhere in circular arc CA31 having a width. That is, the estimation apparatus 100 estimates that the position of the user U2 at the date dt24 is a circular arc CA31 narrowed more than the second circle.

  As described above, the estimation apparatus 100 can narrow down and estimate the position of the user U2 by using information of a plurality of first users other than the user U2. Thus, the estimation apparatus 100 appropriately estimates the position of the user by using information of another user or common behavior information with another user, even if the user has not acquired position information. be able to. Therefore, the estimation device 100 can appropriately estimate the context of the user.

[1-3. When the first user is three or more people]
From here, the case where the position of the user U2 is estimated will be described as an example using FIG. The map information MP31-1 and the map information MP31-2 shown in FIG. 3 are for showing narrowing down of the candidate points of the position of the user U30, and the range (area (area) shown in the map information MP31-1 and the map information MP31-2 ) Are the same area. Further, hereinafter, the map information MP 31-1 and MP 31-2 will be described as map information MP 31 (hereinafter, also simply referred to as “map MP 31”) when the description is made without particular distinction. The triangles shown on the map MP31 indicate the users U31 to U33, respectively. Further, hatched circles shown on the map MP31 indicate candidate points PT31-1 to PT33-2. Each of the candidate points PT31-1 to PT33-2 may be information indicating a position and indicating specific latitude and longitude.

  In the example of FIG. 3, the estimation device 100 acquires road information. In the example of FIG. 3, the road information in the map MP31 is acquired. For example, the estimation device 100 acquires road information in the map MP31 from the road map information storage unit 125 (see FIG. 5). In the example of FIG. 3, the estimation device 100 acquires road information RD31 as shown in the map MP31.

  Further, in the example of FIG. 3, the estimation apparatus 100 acquires information indicating that the user U30 is located near the user U31 at the date dt31. For example, the terminal device 10 used by the user U30 and the terminal device 10 used by the user U31 perform passing communication at the date and time dt31 by a function such as Bluetooth (registered trademark). In addition, the estimation apparatus 100 acquires the position of the user U31 at a predetermined date and time after the date and time dt31. For example, the estimation apparatus 100 acquires the position of the triangle corresponding to the user U31 in the map MP31 of FIG. 3 as the position of the user U31.

  Further, in the example of FIG. 3, the estimation apparatus 100 acquires information indicating that the user U30 is located near the user U32 at the date dt32. For example, the terminal device 10 used by the user U30 and the terminal device 10 used by the user U32 perform passing communication at the date and time dt32 by a function such as Bluetooth (registered trademark). Further, the estimation apparatus 100 acquires the position of the user U32 at a predetermined date and time before the date and time dt32. For example, the estimation apparatus 100 acquires, as the position of the user U32, the position of the triangle corresponding to the user U32 in the map MP31 of FIG.

  Further, in the example of FIG. 3, the estimation apparatus 100 acquires information indicating that the user U30 is located near the user U33 at the date dt33. For example, the terminal device 10 used by the user U30 and the terminal device 10 used by the user U33 perform passing communication at the date and time dt33 by a function such as Bluetooth (registered trademark). In addition, the estimation apparatus 100 acquires the position of the user U33 at a predetermined date and time after the date and time dt33. For example, the estimation apparatus 100 acquires the position of the triangle corresponding to the user U33 in the map MP31 of FIG. 3 as the position of the user U33.

  Then, the estimation apparatus 100 estimates the position of the user U30 at the date and time dt31 to dt33 (step S31). For example, based on the position of user U31 at a predetermined date and time after date and time dt31, and the common action information indicating that user U30 and user U31 approach each other at date and time dt31, estimation device 100 determines the user at date and time dt31 Estimate the position of U30.

  In the example of FIG. 3, the estimation apparatus 100 estimates that the user U30 and the user U31 pass each other at any position on the circle CR31 at the date dt31. Further, the estimation apparatus 100 estimates the position of the user U30 at the date dt31 based on the circle CR31 in FIG. 3 and the road information RD31. Specifically, the estimation apparatus 100 estimates a point (position) where the circle CR31 in FIG. 3 intersects with the road information RD31 as the position of the user U30 at the date dt31. For example, the estimation apparatus 100 estimates a point (position) where the circle CR31 including the points PT31-1 and PT31-2 in FIG. 3 and the road information RD31 intersect as the position of the user U30 at the date dt31.

  For example, based on the position of the user U32 at a predetermined date and time before the date and time dt32 and the common action information indicating that the user U30 and the user U32 approach each other at the date and time dt32, the estimation device 100 determines the user at the date and time dt32 Estimate the position of U30.

  In the example of FIG. 3, the estimation apparatus 100 estimates that the user U30 and the user U32 pass each other at any position on the circle CR32 at the date dt32. Further, the estimation apparatus 100 estimates the position of the user U30 at the date dt32 based on the circle CR32 in FIG. 3 and the road information RD31. Specifically, the estimation apparatus 100 estimates a point (position) where the circle CR32 in FIG. 3 intersects with the road information RD31 as the position of the user U30 at the date and time dt32. For example, the estimation apparatus 100 estimates a point (position) where the circle CR31 including the points PT32-1 to PT32-4 in FIG. 3 and the road information RD31 intersect as the position of the user U30 at the date dt32.

  For example, based on the position of the user U33 at a predetermined date and time after the date and time dt33 and the common action information indicating that the user U30 and the user U33 approach each other at the date and time dt33, the estimation device 100 determines the user at the date and time dt33 Estimate the position of U30.

  In the example of FIG. 3, the estimation apparatus 100 estimates that the user U30 and the user U33 pass each other at any position on the circle CR33 at the date dt33. Further, the estimation apparatus 100 estimates the position of the user U30 at the date dt33 based on the circle CR33 in FIG. 3 and the road information RD31. Specifically, the estimation apparatus 100 estimates a point (position) where the circle CR33 in FIG. 3 intersects with the road information RD31 as the position of the user U30 at the date dt33. For example, the estimation apparatus 100 estimates a point (position) where the circle CR33 including the points PT33-1 and PT33-2 in FIG. 3 intersects the road information RD31 as the position of the user U30 at the date dt33.

  Then, the estimation apparatus 100 narrows down candidates (candidate points) of the position of the user U30 at the dates and times dt31 to dt33 (step S32). For example, the estimation apparatus 100 is based on the positional relationship between the points PT31-1 and PT31-2 at the date dt31, the points PT32-1 to PT32-4 at the date dt32, and the points PT33-1 and PT33-2 at the date dt33. The candidate points at the date and time dt31 to dt33 are narrowed down.

  For example, among the points PT33-1 and PT33-2 at the date and time dt33, the estimation device 100 places the point PT33-1 corresponding to the date and time dt31 closer to the point corresponding to the date and time dt32. Exclude 1 from candidate points. Thereby, for example, the estimation device 100 narrows down the candidate points at the date dt33 to the point PT33-2.

  Then, among the points PT32-1 to PT32-4 at the date and time dt32, the estimation device 100 is not located on the route between the points PT31-1 and PT31-2 at the date and time dt31 and the point PT33-2 at the date and time dt33. PT32-3 and PT32-4 are excluded from the candidate points. Thus, for example, the estimation apparatus 100 narrows down the candidate points at the date and time dt32 to the points PT32-1 and PT32-2.

  As described above, the estimation apparatus 100 can narrow down the position of the user at each date and time with high accuracy by using information of three or more first users. In the example of FIG. 3, the estimation apparatus 100 can accurately estimate the position of the user by narrowing down the candidate points of each date according to the route based on the relationship between the candidate points at the three dates. That is, the estimation apparatus 100 can narrow down the position of the second user with high accuracy by using the information acquired from the terminal devices 10 (multipeers) of the plurality of first users.

  For example, even if the movement of the user is not at the same speed, such as stopping at a signal, the estimation device 100 estimates the movement path by using information on a plurality of first users. It is possible to narrow down the candidates for the position of For example, the estimation apparatus 100 can remove strange data by abnormality detection or the like by using common action information with a plurality of first users. For example, even if the position of the first user acquired by GPS or the like includes an error, the estimation apparatus 100 may narrow down the candidates at each date and time by using information of a plurality of first users. it can. For example, the estimation apparatus 100 can narrow down the candidates at each date and time based on the relationship between the candidates at each date and time by using the information of the plurality of first users. Therefore, the estimation device 100 can appropriately estimate the context of the user.

[1-4. Use of other information]
The example of FIG. 1 shows the case where the position of the user U2 at the date dt12 is estimated based on the position of the user U1 at the date dt11 and the proximity of the user U1 and the user U2 at the date dt12. Other information may be used to improve the estimation accuracy. For example, the estimation apparatus 100 may improve the estimation accuracy of the position of the user U2 at the date dt12 using the schedule information of the user U1 and the schedule information of the user U2.

  For example, the estimation apparatus 100 may improve the estimation accuracy of the position of the user U2 at the date dt12, using the schedule information SC2 of the user U2 shown in the user information storage unit 121 (see FIG. 6). For example, the estimation apparatus 100 estimates that the user U2 is moving from the left side to the right side of the map MP11 when the schedule indicating that the user U2 is positioned on the left side of the map MP11 with respect to the position LC11 at the date dt11 is included. You may Then, the estimation apparatus 100 may estimate that the user U1 and the user U2 approach each other at any position of the left side portion of the circle CR11 at the date and time dt12. That is, the estimation apparatus 100 may estimate that the user U2 is positioned at any position of the left portion of the circle CR11 at the date and time dt12.

  Also, for example, when the estimation device 100 includes a schedule indicating that the user U1 is positioned on the left side of the map MP11 relative to the position LC11 at the date dt13 after the date dt12, the user U1 moves from the right to the left of the map MP11. It may be estimated that it is moving. Then, the estimation apparatus 100 may estimate that the user U1 and the user U2 approach each other at any position of the left side portion of the circle CR11 at the date and time dt12. That is, the estimation apparatus 100 may estimate that the user U2 is positioned at any position of the left portion of the circle CR11 at the date and time dt12. Note that the above is an example, and the estimation device 100 may improve estimation accuracy using various information as appropriate.

[1-5. Other estimation example]
Although the example of estimating the position of the 2nd user as a 2nd user's context was explained as an example in the example of Drawing 1-Drawing 3, estimating device 100 may presume various contexts. For example, the estimation apparatus 100 may estimate the moving means of the second user, the state of the second user, and the like as the context of the second user.

[1-5-1. Estimation of moving means]
For example, the estimation device 100 may estimate the moving means of the user. For example, the estimation apparatus 100 may estimate the moving means of the second user based on the common behavior information of the first user and the second user and the context information of the first user. This point will be described with reference to FIG. FIG. 11 is a diagram illustrating an example of estimation processing according to the embodiment.

  In the example of FIG. 11, the estimation apparatus 100 is based on common behavior information of two first users U61 and U62 and a second user U6, and context information of each of the users U61 and U62. 11 illustrates the case of estimating the moving means (traffic means) of the user U6. In addition, as the moving means mentioned here, it is possible to move the user from one position to another position (carry), various vehicles such as an aircraft including an airplane etc., a vehicle including a bus etc., a railway including a bullet train etc. Means of transport (means of transport) may be included.

  Map information MP61 (hereinafter, also simply referred to as "map MP61") illustrated in FIG. 11 schematically indicates the positions of the user U61, the user U6, and the like. Further, the position LC61 and the position LC62 shown on the map MP61 may be information indicating specific latitude and longitude.

  First, the estimation apparatus 100 (see FIG. 5) acquires common action information indicating that the user U61 and the user U6 are traveling together at the date and time dt 65 (step S61). For example, common action information indicating that the user U61 and the user U6 approach each other multiple times is acquired. For example, in a predetermined period (for example, 15 minutes or one hour) including the date and time dt 65, the estimation device 100 causes the terminal device 10 used by the user U61 and the terminal device 10 used by the user U6 to approach multiple times. Common action information indicating that communication has been performed is acquired.

  For example, the terminal device 10 used by the user U61 and the terminal device 10 used by the user U6 perform passing communication a plurality of times in a predetermined period including the date and time dt 65 by a predetermined function such as NFC. That is, the terminal device 10 used by the user U61 and the terminal device 10 used by the user U6 detect information indicating that the user U61 is located near the user U6 in a predetermined period including the date and time dt65.

  For example, the terminal device 10 used by the user U61 and the terminal device 10 used by the user U6 collect context information indicating that the user U61 is in proximity to the user U6 in a predetermined period including the date and time dt 65, and estimate Transmit to device 100. Note that only one of the terminal device 10 used by the user U61 and the terminal device 10 used by the user U6 transmits context information indicating that the user U61 is close to the user U6 to the estimation device 100 It is also good. Thereby, the estimation device 100 acquires common action information (context information) indicating that the user U61 and the user U6 are accompanied at the date dt65.

  Then, the estimation device 100 acquires context information of the user U 61 at the date and time dt 65 (step S 62). In the example of FIG. 11, the terminal device 10 used by the user U61 detects the predetermined position information such as GPS so that the position of the terminal device 10 (user U61) used by the user U61 at the date and time dt65 is the position LC61. Get context information to indicate that there is. For example, when the terminal device 10 used by the user U61 transmits context information indicating that the position of the user U61 is the position LC61 to the estimation device 100, the estimation device 100 acquires context information of the user U61 at the date dt65. Do.

  Further, the estimation device 100 acquires common action information indicating that the user U62 and the user U6 are traveling together at the date and time dt 67 (step S63). For example, common action information indicating that the user U62 and the user U6 approach each other multiple times is acquired. For example, in a predetermined period (for example, 15 minutes or one hour) including the date and time dt 67, the estimation apparatus 100 causes the terminal device 10 used by the user U62 and the terminal device 10 used by the user U6 to approach multiple times. Common action information indicating that communication has been performed is acquired.

  For example, the terminal device 10 used by the user U62 and the terminal device 10 used by the user U6 perform passing communication a plurality of times in a predetermined period including the date and time dt67 by a predetermined function such as NFC. That is, the terminal device 10 used by the user U62 and the terminal device 10 used by the user U6 detect information indicating that the user U62 is located near the user U6 in a predetermined period including the date and time dt67.

  For example, the terminal device 10 used by the user U62 and the terminal device 10 used by the user U6 collect and estimate context information indicating that the user U62 is close to the user U6 in a predetermined period including the date and time dt67. Transmit to device 100. Note that only one of the terminal device 10 used by the user U62 and the terminal device 10 used by the user U6 transmits context information indicating that the user U62 is close to the user U6 to the estimation device 100 It is also good. Thereby, the estimation apparatus 100 acquires common action information (context information) indicating that the user U62 and the user U6 are accompanied at the date and time dt67.

  Then, the estimation apparatus 100 acquires context information of the user U 62 at the date and time dt 67 (step S 64). In the example of FIG. 11, the terminal device 10 used by the user U62 detects the predetermined position information such as GPS so that the position of the terminal device 10 (user U62) used by the user U62 at the date dt67 is the position LC62. Get context information to indicate that there is. For example, the terminal device 10 used by the user U62 transmits context information indicating that the position of the user U62 is the position LC62 to the estimation device 100, whereby the estimation device 100 acquires context information of the user U62 at the date and time dt67. Do.

  The estimating apparatus 100 estimates the moving means of the user U6 based on the common behavior information of the users U61 and U62 and the user U6 who is the second user, and the position of each of the users U61 and U62 (step S65). ). In the example of FIG. 11, the estimation apparatus 100 indicates that common behavior information indicating that the user U61 and the user U6 are traveling together at the date and time dt65 and that the user U62 and the user U6 are traveling together at the date and time dt67. The moving means between the date and time dt 65 and the date and time dt 67 is estimated using the common behavior information. That is, the estimation apparatus 100 estimates a moving means that moves from the position LC61 of the user U61 (user U6) at the date dt65 to the position LC62 of the user U62 (user U6) at the date dt67.

  For example, the estimation apparatus 100 estimates the moving means of the user U6 based on the distance from the position LC61 to the position LC62 and the elapsed time between the date and time dt65 and the date and time dt67. For example, among the plurality of moving means provided between the position LC61 and the position LC62, the estimating apparatus 100 estimates the moving means corresponding to the elapsed time as the moving means of the user U6.

  In the example of FIG. 11, between the position LC61 and the position LC62, it is assumed that a means of transfer TR61 by bus, a means of transfer TR62 by Shinkansen, and a means of transfer TR63 by airplane are available. For example, the estimation apparatus 100 may use the road map information storage unit 125 (refer to FIG. 5) or the information processing apparatus outside, such as the transportation means TR61 to TR63, regarding the transportation means provided between the points (traveling means information). Get from

  For example, the estimation apparatus 100 estimates the moving means of the user U6 using the moving means information as described above stored in the road map information storage unit 125 (see FIG. 5). For example, the estimation apparatus 100 may estimate the moving means of the user U6 using the moving means information as described above acquired from an external information processing apparatus.

  Further, in the example of FIG. 11, the required time of the moving means TR61 by bus is 5 hours, the required time of the moving means TR62 by Shinkansen is 3 hours, and the required time of the moving means TR63 by airplane is 2 hours I assume. In addition, an elapsed time between the date and time dt65 and the date and time dt67 is 2 hours. Therefore, in the example of FIG. 11, the estimation apparatus 100 estimates the moving means TR63 by the airplane corresponding to the elapsed time "two hours" as the moving means of the user U6.

  Thus, the estimation apparatus 100 appropriately estimates the moving means of the user U6 based on the common behavior information of the users U61 and U62 and the user U6 who is the second user, and the position of each of the users U61 and U62. can do. Therefore, the estimation device 100 can appropriately estimate the context of the user.

[1-5-2. Estimation of state]
Further, the estimation device 100 may estimate the state of the user. For example, the estimation device 100 may estimate the start and the end of the state. For example, the estimation apparatus 100 may estimate the state of the second user based on the transition of the state of the first user. This point will be described below. In the following explanation, “busy” is focused on some kind of thing and is in a state where it can not immediately respond to other things, and “free” is not in a state of being particularly focused but is in a state where it is possible to respond immediately Shall be

  In the following example, as an example of state estimation of the second user, the case of estimating whether the second user can make a call will be described as an example. That is, in the following example, "busy" corresponds to the case where the user is not capable of making telephone calls, and "free" corresponds to the case where the user is capable of making telephone calls.

  As described above, the estimation apparatus 100 can appropriately estimate the state of the second user. Specifically, the estimation apparatus 100 shares a state (state ST1) with a first user (first user BB) from a certain date (date and time XX) of a certain second user (second user AA). Get common behavior information that indicates that. For example, the estimation apparatus 100 acquires schedule information of the second user AA indicating that the second user AA performs a conference call with the first user BB in a period including the date and time XX. For example, the estimation apparatus 100 acquires common behavior information indicating that the first user BB and the second user AA are holding a conference call on the date and time XX.

  Common action information indicating that the first user BB shares a state (state ST2) with another user (user CC) instead of the second user AA from the date and time (date and time XY) after the date and time XX To get For example, the estimation apparatus 100 acquires the schedule information of the first user BB indicating that the conference call is held with the user CC in a period in which the first user BB starts from the date and time XY. For example, the estimation apparatus 100 acquires, as context information of the first user BB, the schedule information of the first user BB indicating that the first user BB holds a conference call with the user CC in a period starting from the date and time XY. .

  Then, the estimation apparatus 100 estimates the context of the second user AA based on the common behavior information of the first user BB and the second user AA at the date and time XX and the context information of the first user BB at the date and time XY. . For example, based on the common behavior information of the first user BB and the second user AA at the date and time XX, and the context information of the first user BB at the date and time XY, the estimation device 100 determines the context of the second user AA at the date and time XY Estimate

  The estimation apparatus 100 performs a conference call with the second user AA at the date and time XX with the other user CC at the date and time XY, so the second user AA makes a phone call at the date and time XY Estimate that the meeting has ended. Then, the estimation apparatus 100 estimates the state of the second user AA at the date and time XY as "free". That is, the estimation apparatus 100 estimates that the second user AA can make a call on the date and time XY.

  As described above, in the example described above, the estimation apparatus 100 determines the date and time XY based on the common behavior information at the date and time XX, which is the second date and time, and the context information of the first user BB at the date and time XY, which is the first date and time. Estimate the context of the second user AA. That is, based on the common behavior of the first user and the second user at the second date and time, and the context information of the first user at the first date and time after the second date and time, the estimation device 100 determines the first 2 Estimate the context of the user. Specifically, the estimation apparatus 100 is based on the common behavior (telephone conference) of the first user and the second user at the second date and time, and the state of the first user at the first date and time (telephone with another user). , Estimate the state (telephone available) of the second user at the first date and time. Therefore, the estimation device 100 can appropriately estimate the context of the user. Further, the estimation apparatus 100 may estimate the state of the second user AA at the date and time XX as “busy”. Note that the above is an example, and the estimation device 100 may estimate the states of various users without being limited to the state in which a telephone call is being made. Also, the above “busy” and “free” are examples, and not limited to “busy” and “free”, other states may be estimated.

[1-6. About the first user]
In addition, the estimation apparatus 100 may select the first user who uses information in the estimation process. For example, the estimation apparatus 100 may select, from among the plurality of first user candidates, a first user who uses information for estimation processing. For example, the estimation apparatus 100 may select first context information to be used for the estimation process. For example, the estimation apparatus 100 may select a first user who uses information for estimation processing among a plurality of first user candidates, and may acquire information of the selected first user. For example, the estimation apparatus 100 may select and acquire first context information used for the estimation process.

  For example, when the second user is performing passing communication (proximity communication) with a plurality of users (candidate users), the estimation apparatus 100 sets the first candidate based on a predetermined condition from the candidate users (candidates of the first user). The user may be selected. For example, the estimation apparatus 100 may select, as the first user, a user who satisfies the predetermined condition among the candidate users.

  For example, the estimation apparatus 100 may not select a user who has run away after passing communication (proximity communication) as the first user. For example, the estimation apparatus 100 may exclude, from the candidate users, users who are estimated to have run away because the moving speed is equal to or higher than a predetermined threshold. For example, the estimation apparatus 100 may exclude, from the candidate users, users who are estimated to have run away as users who do not contribute to improvement in estimation accuracy.

  For example, the estimation apparatus 100 may not select a user who is suddenly stopped, running, or moves irregularly as the first user. For example, the estimation apparatus 100 may exclude, from the candidate users, users whose location information changes irregularly. For example, the estimation apparatus 100 may exclude, from the candidate users, users who do not contribute to the improvement of the estimation accuracy as users whose changes in position information are irregular.

  For example, the estimation apparatus 100 may select the first user from among candidate users excluded from users who do not satisfy the above-mentioned condition regarding estimation accuracy. For example, the estimation apparatus 100 may select, as the first user, a user who is accompanied by the second user among the plurality of first user candidates (candidate users). For example, the estimation apparatus 100 may select a user who has stopped for a predetermined period as the first user among the plurality of first user candidates (candidate users). For example, among the plurality of first user candidates (candidate users), the estimation apparatus 100 may first use, as a first user, a user whose position information within a predetermined range (for example, within 5 m) is continuously detected over a predetermined period. It may be selected as a user. Note that the above is an example, and the estimation apparatus 100 may select the first user from among a plurality of first user candidates (candidate users) using various pieces of information. For example, the estimation apparatus 100 may select the user accompanying the second user or the stationary user as the first user contributing to the improvement of the estimation accuracy.

[1-7. Regarding Use of Second Context Information]
The estimation apparatus 100 may further perform estimation processing using information (estimated information) estimated by the estimation processing. For example, the estimation apparatus 100 may perform the estimation process recursively. That is, the estimation apparatus 100 may perform the estimation process using not only the acquired (detected) context information but also the estimated context information. For example, when the acquired (detected) context information is sparse, the estimating apparatus 100 may perform the estimation process using not only the acquired (detected) context information but also the estimated context information. For example, when the acquired (detected) context information is less than the predetermined amount, the estimating apparatus 100 performs estimation processing using not only the acquired (detected) context information but also the estimated context information. Good.

  For example, the estimating apparatus 100 may calculate a third date and time at a third date and time that is different from both the first date and the second date based on the second user's context information at the second date and time estimated using the first user's context information. The context of the user may be inferred. For example, the estimating apparatus 100 may set the context information of the second user (user U2) at the second date (date dt12) estimated using the context information of the first user (user U1) at the first date (date dt11). The context of the third user (user U3) at the third date and time (date and time dt13) may be estimated based on that. For example, the estimation apparatus 100 may estimate the position of the user U3 who is close to the user U2 at the date dt13, based on the position of the user U2 at the date dt12. Note that the above is an example, and the estimation apparatus 100 may further estimate various information using information (estimated information) estimated by the estimation process.

[1-8. About system configuration]
The system configuration for realizing the above estimation process is not limited to the estimation system 1 shown in FIG. 4 and may be various modes. In the example of FIG. 4, the configuration is provided with the estimation device 100 as a server and the terminal device 10 as a client, and the estimation device 100 and the terminal device 10 are separate bodies (different devices). The terminal device 10 may be integrated. That is, in the estimation system, each terminal device 10 used by the user may be the estimation device 100 that performs the estimation process described above. In this case, the terminal device 10 that is the estimation device 100 may acquire context information and the like from another terminal device 10 during passing communication and the like, and may perform estimation processing based on the acquired context information. Thus, each terminal device 10 may perform communication of context information between the terminal devices 10 without passing through the server device. For example, each terminal device 10 may communicate or share context information between the terminal devices 10 in a mode such as so-called P2P (Peer to Peer).

  Further, the estimation system may be the estimation device 100 in which each of the terminal devices 10 used by the user performs the above-described estimation process, or may include a server device. In this case, the terminal device 10 which is the estimation device 100 may transmit information (estimated information) estimated by the estimation process to the server device, or may acquire information used for the estimation process from the server device. For example, the terminal device 10 may acquire, from the server device, information on moving routes such as map information and flight information. The above is an example, and the estimation system may be realized with any configuration.

[2. Configuration of estimation device]
Next, the configuration of the estimation apparatus 100 according to the embodiment will be described using FIG. FIG. 5 is a diagram showing an example of the configuration of the estimation apparatus according to the embodiment. As shown in FIG. 5, the estimation apparatus 100 includes a communication unit 110, a storage unit 120, and a control unit 130. The estimation apparatus 100 has an input unit (for example, a keyboard or a mouse) that receives various operations from the administrator of the estimation apparatus 100 or the like, and a display unit (for example, a liquid crystal display or the like) for displaying various information. May be

(Communication unit 110)
The communication unit 110 is realized by, for example, a network interface card (NIC). The communication unit 110 is connected to the network by wire or wirelessly, and transmits and receives information to and from, for example, the terminal device 10 included in the estimation system 1.

(Storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory device 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 illustrated in FIG. 5, the storage unit 120 according to the embodiment includes a user information storage unit 121, a context information storage unit 122, a common action information storage unit 123, an estimated information storage unit 124, and a road map information storage unit. And 125. Although not shown, the road map information storage unit 125 uses map information such as map information shown in map MP11 in FIG. 1 and road information such as road RD11, etc. Remember. Further, the map information storage unit 121 may store any information as long as it is information on a map or a road used for the estimation process.

(User information storage unit 121)
The user information storage unit 121 according to the embodiment stores various types of information related to user attributes. For example, the user information storage unit 121 stores user attribute information. FIG. 6 is a diagram illustrating an example of the user information storage unit according to the embodiment. The user information storage unit 121 illustrated in FIG. 6 includes items such as “user ID”, “age”, “sex”, “schedule information”, “walking speed”, and “interest”.

  "User ID" indicates identification information for identifying a user. For example, the user identified by the user ID “U1” corresponds to the user U1 illustrated in the example of FIG. "Age" indicates the age of the user identified by the user ID. The “age” may be a specific age of the user identified by the user ID, such as 35, for example. Also, “sex” indicates the gender of the user identified by the user ID.

  Further, “schedule information” stores schedule information indicating an action schedule of the user identified by the user ID. In the example shown in FIG. 6, “schedule information” shows an abstract code such as “SC1”, but the schedule information stores various information such as the contents of the user's schedule and the date and time (period). Ru. For example, “schedule information” stores information indicating a schedule for a user's conference call, travel, and the like.

  Further, the “walking speed” stores the average walking speed of the user identified by the user ID. In the example shown in FIG. 6, “walking speed” indicates an abstract code such as “WS1”, but a specific numerical value such as “5 km / h (hours per kilometer)” is stored as the walking speed. May be For example, the estimation device 100 may estimate the walking speed of the user from the user's action pattern or the like.

  In addition, when the walking speed corresponding to the user is not stored, the average walking speed of the user having the user attribute to which the user belongs may be used. For example, if the walking speed corresponding to the user U2 is not stored, the user attribute to which the user U2 belongs, that is, the average walking speed of a woman in her twenties may be used.

  Also, “interest” indicates the interest of the user identified by the user ID. That is, “interesting” indicates an object that the user identified by the user ID is highly interested in. In the example shown in FIG. 6, although one “interest” is illustrated for each user, it may be plural.

  For example, in the example illustrated in FIG. 6, the age of the user identified by the user ID "U1" is "twenties", and the gender indicates "male". Also, for example, the user identified by the user ID “U1” indicates that the schedule information is “SC1”. Also, for example, the user identified by the user ID “U1” indicates that the walking speed is “WS1”. Also, for example, the user identified by the user ID “U1” indicates that he / she is interested in “sports”.

  The user information storage unit 121 is not limited to the above, and may store various information according to the purpose. For example, the user information storage unit 121 may store information on demographic attributes of the user and information on psychographic attributes. For example, the user information storage unit 121 may store information such as home position (address), work position (address), name, family structure, income, interest, lifestyle, and the like. First, although not shown in FIG. 6, the user information storage unit 121 may store information identifying the terminal device 10 used by each user in association with the user. For example, the user information storage unit 121 may store information for identifying the terminal device 10-1 used by the user U1 in association with the user U1.

(Context information storage unit 122)
The context information storage unit 122 according to the embodiment stores various information related to the context of the user. FIG. 7 is a diagram illustrating an example of the context information storage unit according to the embodiment. For example, the context information storage unit 122 stores various pieces of context information such as the position of each user, the communication of the terminal device 10, and the user's action. The context information storage unit 122 illustrated in FIG. 7 includes items such as “user ID”, “context ID”, “date and time”, “type”, and “content”.

  "User ID" indicates identification information for identifying a user. For example, the user identified by the user ID “U1” corresponds to the user U1 illustrated in the example of FIG. Also, “context ID” indicates information that identifies the context of the user. “Date and time” indicates the date and time when the context of the corresponding user was performed. In the example of FIG. 7, although illustrated as “dt 11” or the like, a specific date and time such as “Oct 18, 2017 23:41:58” may be stored in the “date and time”. Also, “type” indicates information on the type of context of the corresponding user. Also, “content” indicates the specific content of the context of the corresponding user.

  For example, in the example illustrated in FIG. 7, the user (user U1) identified by the user ID “U1” indicates that the context identified by the context ID “AC11” or the context ID “AC12” has been acquired. .

  For example, in the example illustrated in FIG. 7, as illustrated in the context AC11, the user U1 indicates that context information whose type is the position is acquired at the date and time dt11. The context AC11 indicates that the position of the user U1 at the date and time dt11 is the position “LC11”. In the example shown in FIG. 7, an abstract code such as the position "LC11" is illustrated, but it may be information indicating latitude or longitude. Also, for example, the position “LC11” may be a region name or an address. Thus, when "context AC * (* is any numerical value)" is described, it indicates that the context is the context identified by the context ID "AC *".

  Further, for example, in the example illustrated in FIG. 7, as illustrated in the context AC12, the user U1 indicates that the date information dt12 has acquired context information of the type near field communication. The context AC 12 indicates that the terminal device 10-1 used by the user U1 performs near-field communication with the terminal device 10-2 used by the user U2 at the date and time dt12, that is, the user U1 is located near the user U2 Show. For example, the context AC12 indicates that the user U1 has passed the user U2 at the date dt12.

  Further, for example, in the example illustrated in FIG. 7, as illustrated in the context AC21, the user U2 indicates that, at the date and time dt12, context information whose type is proximity communication is acquired. The context AC 21 indicates that the terminal device 10-2 used by the user U2 performs near-field communication with the terminal device 10-1 used by the user U1 at the date and time dt12, that is, the user U2 is located near the user U1. Show.

  Also, for example, the context AC22 of the user U2 indicates that it is an estimated context EAC1 related to the estimated context. The context AC22 indicates that the position of the user U2 at the date dt12 is estimated to be any one on the circle CR11.

  The context information storage unit 122 is not limited to the above, and may store various information according to the purpose. Although FIG. 7 shows the case where context information is stored in the context information storage unit 122 for each user ID, the context information is not limited to each user ID, and may be stored, for example, in time sequence.

(Common action information storage unit 123)
The common action information storage unit 123 according to the embodiment stores various pieces of information on common actions. FIG. 8 is a diagram illustrating an example of the common behavior information storage unit according to the embodiment. The common action information storage unit 123 illustrated in FIG. 8 includes items such as “common action ID”, “content”, “user ID”, “date and time”, “context ID”, and “action summary”.

  The “common action ID” indicates identification information for identifying a common action. "Content" indicates the content of the common action identified by the common action ID.

  The “user ID” indicates identification information for identifying the user extracted as the user who has performed the common action identified by the common action ID. For example, the user U1 and the user U2 correspond to the user U1 and the user U2 illustrated in the example of FIG. Note that the number of users who perform the common action may be three or more.

  “Date and time” indicates the date and time when the context of the corresponding user was performed. Also, “context ID” indicates information identifying the context of the user extracted as the common action. For example, the context AC12 and the context AC21 correspond to the context related to the near field communication of the terminal device 10-1 and the terminal device 10-2 in step S12 illustrated in the example of FIG. 1. Also, “action summary” indicates a summary of common actions performed by the corresponding user.

  For example, in the example illustrated in FIG. 8, the content of the common behavior information (common behavior information CM1) identified by the common behavior ID “CM1” indicates that the content is “proximity”. The common behavior information CM1 indicates that it is information (context information) extracted on condition that the user is in proximity. It shows that the user U1 and the user U2 are extracted as the user who has performed the action corresponding to the common action information CM1. Also, the user U1 and the user U2 indicate that they have approached at the date and time dt12. It also indicates that the user U6 and the user U61 have been extracted as the users who have performed the action corresponding to the common action information CM1. Further, the user U6 and the user U61 indicate that they approach each other at the date dt65.

  The common behavior information storage unit 123 may store various information according to the purpose, not limited to the above.

(Estimated information storage unit 124)
The estimated information storage unit 124 according to the embodiment stores various types of estimated information. FIG. 9 is a diagram illustrating an example of the estimated information storage unit according to the embodiment. The estimated information storage unit 124 illustrated in FIG. 9 is a diagram illustrating an example of the estimated information storage unit according to the embodiment. The estimated information storage unit 124 stores information on the estimated context (estimated context). For example, the estimated information storage unit 124 stores various estimated context information such as the position of each user, the communication of the terminal device 10, the action of the user, and the like. The estimated information storage unit 124 illustrated in FIG. 9 includes items such as “user ID”, “estimated context ID”, “date and time”, “type”, and “content”.

  "User ID" indicates identification information for identifying a user. For example, the user identified by the user ID “U1” corresponds to the user U1 illustrated in the example of FIG. Also, “estimated context ID” indicates information identifying a context (estimated context) of the estimated user. "Date" indicates the date corresponding to the estimated context. Also, “type” indicates information regarding the type of estimated context of the corresponding user. Also, “content” indicates the specific content of the corresponding user's estimated context.

  For example, in the example shown in FIG. 9, the user U2 indicates that the context (estimated context) identified by the estimated context ID "EAC1" has been estimated. For example, in the example illustrated in FIG. 9, as indicated by the estimated context EAC1, the user U2 indicates that, at the date dt12, context information whose type is the position is estimated. The estimated context EAC1 indicates that the position of the user U2 at the date and time dt12 is estimated to be anywhere on the circle CR11. Thus, when stated as "estimated context EAC * (* is any numerical value)", it indicates that the estimated context is the estimated context identified by the estimated context ID "EAC *".

  The estimated information storage unit 124 is not limited to the above, and may store various information according to the purpose. Although FIG. 9 shows a case where estimated context information is stored in the estimated information storage unit 124 for each user ID, estimated context information is not limited to each user ID, and may be stored, for example, in time order.

(Control unit 130)
Returning to the description of FIG. 5, the control unit 130 is a controller, and is stored in a storage device inside the estimation apparatus 100 by, for example, a central processing unit (CPU) or a micro processing unit (MPU). Various programs (corresponding to an example of an estimation program) are realized by executing the RAM as a work area. The control unit 130 is a controller, and is realized by, for example, an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

  As illustrated in FIG. 5, the control unit 130 includes an acquisition unit 131, an estimation unit 132, and a provision unit 133, and implements or executes the functions and operations of the information processing described below.

(Acquisition unit 131)
The acquisition unit 131 acquires various types of information. For example, the acquisition unit 131 acquires various types of information from the storage unit 120. For example, the acquisition unit 131 acquires various types of information from the user information storage unit 121, the context information storage unit 122, the common behavior information storage unit 123, the estimation information storage unit 124, and the road map information storage unit 125.

  For example, the acquisition unit 131 acquires various types of information from the terminal device 10. For example, the acquisition unit 131 acquires context information of the user from the terminal device 10. For example, the acquisition unit 131 acquires information related to communication with another terminal device 10 from the terminal device 10. For example, the acquisition unit 131 acquires context information indicating that proximity communication has been performed with another terminal device 10 from the terminal device 10.

  For example, the acquisition unit 131 acquires behavior information of the user from the terminal device 10. The acquisition unit 131 acquires position information of the user. For example, the acquisition unit 131 acquires common behavior information of the user from the terminal device 10 or an external information processing device.

  For example, the acquisition unit 131 may include common action information indicating that the first user and the second user have performed common actions that are common actions, and first context information indicating the context of the first user at the first date and time. To get The acquisition unit 131 acquires first context information indicating the position of the first user at the first date and time. The acquisition unit 131 acquires first context information indicating the state of the first user at the first date and time.

  For example, the acquisition unit 131 acquires common action information indicating that the first user and the second user are located within the predetermined range at the same date and time. The acquisition unit 131 is common behavior information detected by performing predetermined proximity communication between the first terminal used by the first user and the second terminal used by the second user, and Common action information indicating that the second user approaches is acquired.

  For example, the acquisition unit 131 acquires first context information of the first user at the first date and time that is a date and time before the second date and time. The acquisition unit 131 acquires first context information of the first user at the first date and time, which is a date and time later than the second date and time.

  For example, the acquisition unit 131 acquires common action information indicating that the first user and the second user performed the common action at the second date and time. The acquisition unit 131 acquires common action information indicating that the first user and the second user have performed common actions at the first date and time. The acquisition unit 131 includes a plurality of common action information indicating that each of the plurality of first users and the second user performed the common action, and a plurality of pieces of information on a plurality of first dates and times corresponding to the plurality of first users. Obtaining a plurality of pieces of first context information indicating context of each of the first users of

  Further, the acquisition unit 131 acquires common action information indicating that the first user and the second user browse the same content within a predetermined period. For example, the acquisition unit 131 acquires common action information indicating that the first user and the second user browse the same content within a predetermined period on the Internet.

  Also, for example, the acquiring unit 131 indicates that the other first user different from the first user and the second user perform another common action at another first date and time different from the first date and time. Common behavior information and other first context information indicating the context of another first user at another first date and time are acquired. For example, the acquisition unit 131 acquires second context information indicating the context of the second user at a third date and time different from the second date and time.

  In the example of FIG. 1, the acquisition unit 131 acquires context information of the user U1 at the date and time dt11. For example, the acquisition unit 131 acquires context information indicating that the position of the user U1 is the position LC11 from the terminal device 10-1. Further, the acquisition unit 131 acquires common action information (context information) indicating that the user U1 and the user U2 approach each other at the date and time dt12. For example, the acquisition unit 131 acquires common action information indicating that the user U1 and the user U2 have passed each other at the date and time dt12. For example, the acquisition unit 131 may select and acquire a first user who uses information in the estimation process. For example, the estimation unit 132 may select a first user who uses information for estimation processing among the plurality of first user candidates, and may acquire information of the selected first user. For example, the estimation unit 132 may select and acquire first context information used for estimation processing.

(Estimater 132)
The estimation unit 132 estimates various information. For example, the estimation unit 132 estimates various information based on the information stored in the storage unit 120. The estimation unit 132 estimates various information based on the information stored in the user information storage unit 121, the context information storage unit 122, the common behavior information storage unit 123, the estimation information storage unit 124, and the road map information storage unit 125. Do. For example, the estimation unit 132 estimates the context of the user using the information acquired by the acquisition unit 131.

  The estimation unit 132 estimates the context of the second user at the second date and time different from the first date and time, based on the common behavior information and the first context information acquired by the acquisition unit 131. Further, the estimation unit 132 estimates a context including the position of the second user at the second date and time. The estimation unit 132 estimates the state of the second user at the second date and time as the context of the second user. The estimation unit 132 estimates the moving means used by the second user at the second date and time as the second user's context. The estimation unit 132 estimates the context of the second user at the second date and time that is different from any of the multiple first date and times based on the plurality of common behavior information acquired by the acquisition unit 131 and the plurality of pieces of first context information. .

  The estimation unit 132 estimates the context of the second user at the second date and time based on the common behavior information, the first context information, the other common behavior information, and the other first context information. The estimation unit 132 estimates the context of the second user at the second date and time between the first date and time and the other first date and time. The estimation unit 132 estimates the context of the second user at the second date and time based on the second context information.

  In the example of FIG. 1, the estimation unit 132 calculates the position LC11 of the user U1 at the date dt11 and the common action information indicating that the user U1 and the user U2 approach each other at the date dt12. Estimate the position. For example, estimation unit 132 performs proximity communication with user U1 based on position LC11 of user U1 at date dt11 and common action information indicating that user U1 and user U2 approach at date dt12. Estimate the position.

  In the example of FIG. 1, the estimation unit 132 estimates the position of the user U2 at the date dt12 based on the elapsed time between the date dt11 and the date dt12 and the walking speed of the user U1. For example, the estimation unit 132 estimates the movable range of the user U1 from the position LC11 in the elapsed time based on the walking speed WS1 of the user U1 as shown in the user information storage unit 121 (see FIG. 6). In addition, when the estimation unit 132 does not have the walking speed corresponding to the user U1, the user U1 moves from the position LC11 in the elapsed time based on the user attribute to which the user U1 belongs, that is, the average walking speed of a 20's male. The possible range may be estimated.

  For example, when the walking speed of the user U1 is “6 km / h (kilometers per hour)” and the elapsed time between the date and time dt11 and the date and time dt12 is 30 minutes, the estimation unit 132 determines that the user U1 is in the elapsed time It is estimated that it can move by about "3 km (= 6 * 0.5)". In this case, the estimation unit 132 estimates that the user U1 and the user U2 have passed each other around a radius of 3 km centered on the position LC11.

  In the example of FIG. 1, the estimation unit 132 estimates that the user U1 and the user U2 pass each other at any position on the circle CR11 at the date dt12. That is, the estimation unit 132 estimates that the position of the user U2 at the date and time dt12 is any position on the circle CR11.

(Provision unit 133)
The providing unit 133 provides various information to an external information processing apparatus. For example, the providing unit 133 provides various types of information to the terminal device 10. The providing unit 133 provides a service using the information estimated by the estimating unit 132. For example, the providing unit 133 provides a service using the context of the user estimated by the estimating unit 132. The providing unit 133 provides a service using information on the context of the second user at the second date and time estimated by the estimating unit 132.

  For example, the providing unit 133 provides a service for distributing content using the estimated user context. For example, the providing unit 133 provides the terminal device 10 with content using the estimated user context. For example, the providing unit 133 provides an advertisement to the terminal device 10 according to the estimated position of the user. For example, the providing unit 133 provides the terminal device 10 with navigation information for providing guidance from the estimated position of the user to the position of the nearest station or facility.

[3. Flow of estimation process]
Here, the procedure of the estimation process by the estimation apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 10 is a flowchart illustrating an example of estimation processing according to the embodiment.

  As shown in FIG. 10, the estimation apparatus 100 acquires common action information indicating that the first user and the second user have performed the common action that is the common action (step S101). In the example of FIG. 1, for example, the estimation device 100 acquires common behavior information between the user U1 and the user U2 from the common behavior information storage unit 123 (see FIG. 8).

  Further, the estimation apparatus 100 acquires first context information indicating the context of the first user at the first date and time (step S102). In the example of FIG. 1, for example, the estimation apparatus 100 acquires context information AC11 indicating that the position of the user U1 at the date dt11 is the position LC11 from the context information storage unit 122 (see FIG. 7).

  Then, the estimation apparatus 100 estimates the context of the second user at a second date and time different from the first date and time, based on the common behavior information and the first context information (step S103). In the example of FIG. 1, for example, the estimation apparatus 100 estimates that the position of the user U2 at the date and time dt12 is any one on the circle CR11.

  Then, the estimation apparatus 100 provides a service based on the context of the second user (step S104). For example, the estimation apparatus 100 provides the terminal device 10-2 used by the user U2 with content such as an advertisement according to the estimated position of the user U2.

[4. effect〕
As described above, the estimation apparatus 100 according to the embodiment includes the acquisition unit 131 and the estimation unit 132. The acquisition unit 131 is common action information indicating that the first user (for example, the user U1 in the embodiment) and the second user (for example, the user U2 in the embodiment) perform a common action that is a common action. And first context information indicating the context of the first user at the first date and time. The estimation unit 132 estimates the context of the second user at the second date and time different from the first date and time, based on the common behavior information and the first context information acquired by the acquisition unit 131.

  Thus, the estimation apparatus 100 according to the embodiment is different from the first date and time based on the common behavior information of the first user and the second user and the first context information of the first user at the first date and time. By estimating the context of the second user at the second date and time, it is possible to properly estimate the context of the user (the same applies to the “second user” and the like).

  In addition, in the estimation device 100 according to the embodiment, the acquisition unit 131 acquires first context information indicating the position of the first user at the first date and time.

  Thus, the estimation apparatus 100 according to the embodiment can appropriately estimate the context of the user by acquiring the first context information indicating the position of the first user at the first date and time.

  Further, in the estimation device 100 according to the embodiment, the estimation unit 132 estimates a context including the position of the second user at the second date and time.

  Thus, the estimation apparatus 100 according to the embodiment can appropriately estimate the context of the user by estimating the context including the position of the second user at the second date and time.

  Further, in the estimation apparatus 100 according to the embodiment, the acquisition unit 131 acquires first context information indicating the state of the first user at the first date and time.

  As described above, the estimation apparatus 100 according to the embodiment can appropriately estimate the context of the user by acquiring the first context information indicating the state of the first user at the first date and time.

  Further, in the estimation device 100 according to the embodiment, the estimation unit 132 estimates the state of the second user at the second date and time as the context of the second user.

  Thus, the estimation apparatus 100 according to the embodiment can appropriately estimate the context of the user by estimating the context including the position of the second user at the second date and time.

  Further, in the estimation device 100 according to the embodiment, the estimation unit 132 estimates the moving means used by the second user at the second date and time as the context of the second user.

  Thus, the estimation apparatus 100 according to the embodiment can appropriately estimate the context of the user by estimating the moving means used by the second user at the second date and time as the context of the second user. .

  Further, in the estimation device 100 according to the embodiment, the acquisition unit 131 acquires common behavior information indicating that the first user and the second user are located within the predetermined range at the same date and time.

  Thus, the estimation device 100 according to the embodiment appropriately estimates the context of the user by acquiring common action information indicating that the first user and the second user are located within the predetermined range at the same date and time. can do.

  In the estimation device 100 according to the embodiment, the acquisition unit 131 is a first terminal (for example, the terminal device 10-1 in the embodiment) used by the first user and a second terminal (second embodiment) used by the second user. In the embodiment, common action information detected by, for example, the terminal device 10-2) performing predetermined proximity communication, the common action information indicating that the first user and the second user are close to each other get.

  Thus, the estimation apparatus 100 according to the embodiment is common action information detected by the first terminal used by the first user and the second terminal used by the second user performing predetermined proximity communication. The context of the user can be appropriately estimated by acquiring common behavior information indicating that the first user and the second user are close to each other.

  In addition, in the estimation device 100 according to the embodiment, the acquisition unit 131 acquires first context information of the first user at the first date and time that is a date and time before the second date and time.

  As described above, the estimation apparatus 100 according to the embodiment appropriately estimates the context of the user by acquiring the first context information of the first user at the first date and time that is the date and time before the second date and time. Can.

  Further, in the estimation apparatus 100 according to the embodiment, the acquisition unit 131 acquires first context information of the first user at the first date and time that is a date and time after the second date and time.

  As described above, the estimation apparatus 100 according to the embodiment appropriately estimates the context of the user by acquiring the first context information of the first user at the first date and time that is the date and time after the second date and time. Can.

  In addition, in the estimation device 100 according to the embodiment, the acquisition unit 131 acquires common action information indicating that the first user and the second user performed the common action at the second date and time.

  As described above, the estimation apparatus 100 according to the embodiment appropriately estimates the context of the user by acquiring common action information indicating that the first user and the second user performed the common action at the second date and time. can do.

  In addition, in the estimation device 100 according to the embodiment, the acquisition unit 131 acquires common action information indicating that the first user and the second user performed the common action at the first date and time.

  Thus, the estimation apparatus 100 according to the embodiment appropriately estimates the context of the user by acquiring common action information indicating that the first user and the second user have performed common action at the first date and time. can do.

  Further, in the estimation device 100 according to the embodiment, the acquiring unit 131 is configured to include a plurality of common behavior information indicating that each of the plurality of first users and the second user performed a common behavior, and a plurality of first users. A plurality of pieces of first context information indicating contexts of a plurality of first users at a plurality of corresponding first date and time are acquired. The estimation unit 132 estimates the context of the second user at the second date and time that is different from any of the multiple first date and times based on the plurality of common behavior information acquired by the acquisition unit 131 and the plurality of pieces of first context information. .

  As described above, the estimation apparatus 100 according to the embodiment includes the plurality of common behavior information of each of the plurality of first users and the second user, and the plurality of plurality of first dates and times corresponding to each of the plurality of first users. The context of the user can be appropriately estimated by estimating the context of the second user at a second date and time that is different from any of the multiple first dates and times based on the first context information.

  Further, in the estimation apparatus 100 according to the embodiment, the providing unit 133 provides a service using information on the context of the second user at the second date and time estimated by the estimation unit 132.

  Thus, the estimation apparatus 100 according to the embodiment can provide an appropriate service according to the context of the user by providing the service using the information on the context of the second user at the second date and time.

[5. Hardware configuration]
The estimation apparatus 100 according to the embodiment described above is realized by, for example, a computer 1000 configured as shown in FIG. FIG. 12 is a hardware configuration diagram showing an example of a computer for realizing the function of the estimation device. The computer 1000 includes a CPU 1100, a RAM 1200, a ROM 1300, a hard disk drive (HDD) 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

  The CPU 1100 operates based on a program stored in the ROM 1300 or the HDD 1400 to control each part. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 starts up, a program depending on the hardware of the computer 1000, and the like.

  The HDD 1400 stores a program executed by the CPU 1100, data used by the program, and the like. The communication interface 1500 receives data from another device via the network N, sends the data to the CPU 1100, and provides data generated by the CPU 1100 to the other device via the network N.

  The CPU 1100 controls an output device such as a display or a printer and an input device such as a keyboard or a mouse via the input / output interface 1600. The CPU 1100 acquires data from an input device via the input / output interface 1600. The CPU 1100 also outputs the generated data to the output device via the input / output interface 1600.

  The media interface 1700 reads a program or data stored in the recording medium 1800 and provides the CPU 1100 with the program via the RAM 1200. The CPU 1100 loads such a program from the recording medium 1800 onto the RAM 1200 via the media interface 1700 and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a digital versatile disc (DVD) or a phase change rewritable disc (PD), an optical magnetic recording medium such as a magneto-optical disk (MO), a tape medium, a magnetic recording medium Etc.

  For example, when the computer 1000 functions as the estimation device 100 according to the embodiment, the CPU 1100 of the computer 1000 realizes the function of the control unit 130 by executing a program loaded on the RAM 1200. The CPU 1100 of the computer 1000 reads these programs from the recording medium 1800 and executes them, but as another example, these programs may be acquired from another device via the network N.

  Although the embodiments of the present application have been described above in detail based on the drawings, these are only examples, and various modifications and improvements can be made based on the knowledge of those skilled in the art, including the embodiments described in the rows of the disclosure of the invention. It is possible to practice the invention in other forms as well.

[6. Other]
Further, among the processes described in the above embodiment, all or part of the process described as being automatically performed may be manually performed, or the process described as being manually performed. All or part of them can be performed automatically by known methods. In addition, information including processing procedures, specific names, various types of data and parameters shown in the above-mentioned document and drawings can be generated arbitrarily unless otherwise specified. For example, the various information shown in each figure is not limited to the illustrated information.

  Further, each component of each device illustrated is functionally conceptual, and does not necessarily have to be physically configured as illustrated. That is, the specific form of the distribution and integration of each device is not limited to the illustrated one, and all or a part thereof may be functionally or physically dispersed in any unit depending on various loads, usage conditions, etc. It can be integrated and configured.

  In addition, the processes described in the above-described embodiment can be appropriately combined within the range in which the process contents do not conflict.

  In addition, the "section (module, unit)" described above can be read as "means" or "circuit". For example, the acquisition unit can be read as an acquisition unit or an acquisition circuit.

DESCRIPTION OF SYMBOLS 1 estimation system 100 estimation device 121 user information storage unit 122 context information storage unit 123 common behavior information storage unit 124 estimation information storage unit 130 control unit 131 acquisition unit 132 estimation unit 133 provision unit 10 terminal device N network

Claims (16)

An acquisition unit configured to acquire common action information indicating that the first user and the second user performed common action that is common action, and first context information indicating a context of the first user at a first date and time; ,
An estimation unit configured to estimate a context of the second user at a second date and time different from the first date and time based on the common behavior information acquired by the acquisition unit and the first context information;
An estimation apparatus comprising: The acquisition unit
The estimation apparatus according to claim 1, wherein the first context information indicating the position of the first user at the first date and time is acquired. The estimation unit
The estimation apparatus according to claim 1 or 2, wherein a context including the position of the second user at the second date and time is estimated. The acquisition unit
The estimation apparatus according to claim 1, wherein the first context information indicating a state of the first user at the first date and time is acquired. The estimation unit
The estimation apparatus according to claim 1 or 4, wherein a state of the second user at the second date and time is estimated as a context of the second user. The estimation unit
The estimation device according to claim 1 or 2, wherein the moving means used by the second user at the second date and time is estimated as a context of the second user. The acquisition unit
The estimation device according to any one of claims 1 to 6, wherein the common action information indicating that the first user and the second user are located within a predetermined range at the same date and time is acquired. . The acquisition unit
The common action information detected by performing predetermined proximity communication between the first terminal used by the first user and the second terminal used by the second user, the first user and the common user The estimation device according to any one of claims 1 to 7, wherein the common action information indicating that the second user approaches is acquired. The acquisition unit
The estimation device according to any one of claims 1 to 8, wherein the first context information of the first user at the first date and time, which is a date and time before the second date and time, is acquired. The acquisition unit
The estimation apparatus according to any one of claims 1 to 8, wherein the first context information of the first user at the first date and time, which is a date and time later than the second date and time, is acquired. The acquisition unit
The common action information indicating that the first user and the second user performed the common action at the second date and time is acquired. The method according to any one of claims 1 to 10, Estimator. The acquisition unit
The common action information indicating that the first user and the second user performed the common action at the first date and time is acquired. The method according to any one of claims 1 to 10, Estimator. The acquisition unit
The plurality of common behavior information indicating that each of the plurality of first users and the second user performed the common behavior, and the plurality of first behaviors at the plurality of first dates and times corresponding to the plurality of first users. Obtaining a plurality of first context information indicating the context of each of the users;
The estimation unit
Estimating the context of the second user at a second date and time different from any of the first dates and times based on the plurality of common behavior information acquired by the acquisition unit and the plurality of first context information. The estimation apparatus according to any one of claims 1 to 12, characterized by A providing unit for providing a service using information on the context of the second user at the second date and time estimated by the estimation unit;
The estimation apparatus according to any one of claims 1 to 13, further comprising: A computer implemented estimation method,
An acquisition step of acquiring common action information indicating that the first user and the second user performed common action that is common action, and first context information indicating the context of the first user at a first date and time; ,
Estimating the context of the second user at a second date and time different from the first date and time based on the common behavior information and the first context information acquired by the acquisition step;
Estimation method characterized by including. An acquisition procedure for acquiring common action information indicating that the first user and the second user performed common action that is common action, and first context information indicating the context of the first user at a first date and time; ,
An estimation procedure for estimating the context of the second user at a second date and time different from the first date and time based on the common action information acquired by the acquisition procedure and the first context information;
An estimation program that causes a computer to execute.

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