JP2012079265A - Relationship determination device, relationship determination system, relationship determination method, and relationship determination program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To accurately determine a predetermined relationship between persons from an object that includes information associated with a plurality of persons.SOLUTION: A relationship determination device includes: a dispersion value calculation part for receiving an object associated with at least two specific user identifiers of user identifiers capable of identifying persons and position information and time information associated with the object, and calculating a dispersion value of a position and a dispersion value of a time on the basis of the received position information and time information; and a relationship determination part for determining to have a predetermined relationship between persons identified by the specific user identifiers, when the dispersion value of the position is equal to or more than a first threshold value and the dispersion value of the time is equal to or more than a second threshold value.

Description

  The present invention relates to a technique for determining a relationship between persons.

  A technique for determining a relationship between persons from an object including information on a plurality of persons is known.

  For example, the technique described in Patent Literature 1 recognizes a person's face image from a plurality of images in which a person is photographed, and identifies each person photographed for each image. In this technique, a correlation value representing the degree of familiarity is set between persons, which increases as the frequency of appearing together in one image increases.

  Further, the technique described in Patent Document 2 specifies the degree of association between persons based on the information of the organization to which each person belongs and the description order of authors and joint names included in the copyrighted work.

  Further, the technique described in Patent Document 3 calculates an evaluation value indicating a relationship between persons based on the appearance frequency of persons appearing in a moving image and the period in which specific persons appear simultaneously.

JP 2008-071112 A JP 2010-086229 A JP 2010-140069 A

  However, in any of the related technologies described above, when there are many objects created in a specific environment, a certain human relationship is specified based on information of a plurality of persons included in the object. Therefore, any of the related techniques described above erroneously determines that there is an intimate friendship among persons who are only related in a specific environment.

  Therefore, none of the related techniques described above can accurately determine a predetermined relationship between persons from an object including information on a plurality of persons.

  One of the objects of the present invention is to provide a relationship determination device, a relationship determination system, a relationship determination method, and a relationship determination program capable of determining a predetermined relationship between persons with high accuracy from an object including information on a plurality of persons. is there.

  The first relationship determination device according to one aspect of the present invention includes an object associated with at least two specific user identifiers among user identifiers capable of identifying a person, position information and time information associated with the object, A variance value calculation unit that calculates a variance value of a location and a variance value of a time based on the received location information and time information, and the variance value of the location is greater than or equal to a first threshold, and the variance value of the time A relationship determination unit that determines that there is a predetermined relationship between the persons identified by the specific user identifier when is equal to or greater than a second threshold.

  A first relationship determination system according to an aspect of the present invention includes an object including feature information that is information that can identify a person, a user terminal that transmits position information indicating a position, and time information indicating a time, and a person An object storage unit that stores an object associated with a user identifier that can be identified, position information indicating a certain position, and time information indicating a certain time in association with each other, and a relationship determination device, An apparatus includes: an object receiving unit that receives an object, position information, and time information from the user terminal; and a user that can identify a person identified by the feature information based on feature information included in the object received by the object receiving unit. The identifier is acquired, and the object, the user identifier, and the object reception unit The object-related person acquisition unit that stores the position information and the time information received together with the user information in the object storage unit, and the user identifier received from the user terminal, An object associated with at least two user identifiers and position information and time information associated with the object are read, and a position variance value and a time variance value based on the read position information and time information. Between the person identified by the at least two user identifiers when the variance value at the position is greater than or equal to a first threshold value and the variance value at the time is greater than or equal to a second threshold value Are determined to have a predetermined relationship and are associated with the at least two user identifiers. It includes a relationship determination unit for generating information indicating the engagement, wherein the user terminal outputs said information indicating said predetermined relationship to said relationship judging unit has generated at least two user identifiers.

  A first relationship determination method according to one aspect of the present invention includes an object associated with at least two specific user identifiers among user identifiers that can identify a person, position information and time information associated with the object, The position variance value and the time variance value are calculated based on the received location information and time information, the location variance value is equal to or greater than a first threshold value, and the time variance value is a second threshold value. If it is above, it is determined that there is a predetermined relationship between the persons identified by the specific user identifier.

  A first relationship determination program according to an aspect of the present invention includes an object in which at least two specific user identifiers among user identifiers capable of identifying a person are associated with a computer, position information associated with the object, and Processing for receiving time information, calculating a position variance value and a time variance value based on the received position information and time information, and the position variance value is equal to or greater than a first threshold, and the time variance value And determining that there is a predetermined relationship between the persons identified by the specific user identifier when the value is equal to or greater than a second threshold.

  An example of the effect of the present invention is that a predetermined relationship between persons can be determined with high accuracy from an object including information on a plurality of persons.

FIG. 1 is a block diagram illustrating the configuration of the relationship determination apparatus according to the first embodiment. FIG. 2 is a diagram illustrating an example of information stored in the object storage unit. FIG. 3 is a flowchart illustrating an example of an outline of the operation of the relationship determination device according to the first embodiment. FIG. 4 is a diagram illustrating an example in which the relationship determination device according to the first embodiment includes an object storage unit. FIG. 5 is a block diagram illustrating an example of the configuration of the relationship determination device according to the third modification of the first embodiment. FIG. 6 is a block diagram showing the configuration of the relationship determination system in the second embodiment. FIG. 7 is a block diagram illustrating a configuration of the relationship determination apparatus according to the second embodiment. FIG. 8 is a diagram illustrating an example of information stored in the face ID storage unit. FIG. 9 is a diagram illustrating an example of a determination result in which the relationship determination unit determines the relationship based on the variance value. FIG. 10 is a diagram illustrating an example of a determination result in which the relationship determination unit determines the relationship based on the variance value. FIG. 11 is an example of information output by the user terminal. FIG. 12 is another example of information output by the user terminal. FIG. 13 is another example of information output by the user terminal. FIG. 14 is a diagram illustrating an example of an outline of the operation of the relationship determination system according to the second embodiment. FIG. 15 is a diagram illustrating an example of an outline for correcting a category boundary line based on information of input data input from a person X with a user terminal. FIG. 16 is a diagram illustrating an example of user information stored in the address book. FIG. 17 is a diagram illustrating an example in which a person is classified into a predetermined category based on a position variance value and a time variance value. FIG. 18 is a diagram illustrating an example of an operation for determining the relationship between a person Z who is not registered in the address book and a specific person who is the owner of the address book. FIG. 19 is a diagram showing an example of a message for prompting the person Z to be registered in the group “circle” with the address book. FIG. 20 is a block diagram showing the configuration of the relationship determination system in the third embodiment. FIG. 21 is a block diagram illustrating a configuration of the relationship determination device according to the third embodiment. FIG. 22 is a diagram illustrating an example of information stored in the live activity line information storage unit. FIG. 23 is a diagram illustrating an example of the live activity line divergence degree specified by the live activity line divergence degree calculation unit based on the shortest distance. FIG. 24 shows the result of calculating the position variance value, the time variance value, and the average value of the live activity line divergence based on the objects associated with the user identifiers of the persons M and N with the variance value calculation unit. It is a figure which shows an example. FIG. 25 is a diagram illustrating an example of a new divergence degree calculated by the variance value calculation unit. FIG. 26 is a diagram illustrating an example of an outline of the operation of the relationship determination system according to the third embodiment. FIG. 27 is a block diagram showing the configuration of the relationship determination system in the fourth embodiment. FIG. 28 is a block diagram showing the configuration of the relationship determination apparatus in the fourth embodiment. FIG. 29 is a diagram illustrating an example of the degree of friends output by the user terminal. FIG. 30 is a diagram illustrating an example of an outline of operations different from those in the second embodiment of the relationship determination system in the fourth embodiment. FIG. 31 is a block diagram illustrating an example of the configuration of the relationship determination system in the first modification example of the fourth embodiment.

  Embodiments for carrying out the present invention will be described in detail with reference to the drawings. In each embodiment described in each drawing and specification, the same reference numerals are given to components having the same function.

[First embodiment]
FIG. 1 is a block diagram showing the configuration of the relationship determination apparatus 100 according to the first embodiment of the present invention. Referring to FIG. 1, the relationship determination apparatus 100 includes a variance value calculation unit 104 and a relationship determination unit 105.

  The relationship determination apparatus 100 according to the first embodiment reads an object associated with at least two specific user identifiers, position information associated with the object, and time information from the storage unit. Then, the relationship determination apparatus 100 calculates a position variance value and a time variance value based on the read position information and time information. The relationship determination apparatus 100 determines whether the position variance value is greater than or equal to the first threshold value and the time variance value is greater than or equal to the second threshold value. It is determined that there is a predetermined relationship. With this configuration, the relationship determination apparatus 100 according to the first embodiment can determine a predetermined relationship between persons with high accuracy from an object including information on a plurality of persons.

  Hereinafter, each component with which the relationship determination apparatus 100 is provided is demonstrated.

=== Dispersion Value Calculation Unit 104 ===
The distributed value calculation unit 104 receives a user identifier from another functional unit not shown in FIG. Then, the variance value calculation unit 104 stores an object associated with two or more specific user identifiers among the received user identifiers, the above-described specific user identifier, position information, and time information in an object storage not shown in FIG. Read from the section.

  The object storage unit stores an object, a user identifier capable of identifying a certain person, position information indicating a certain position, and time information indicating a certain time in association with each other. FIG. 2 is a diagram illustrating an example of information stored in the object storage unit. Referring to FIG. 2, the object storage unit stores an object identifier, an object entity, position information, time information, and a user list in association with each other. Although not shown in FIG. 2, the object storage unit may store different types of objects such as photographs and brochures as object entities.

  The object identifier is an identifier of an object that can uniquely identify an associated object entity. The object entity is the object data itself. The object includes all kinds of information such as a photograph, an image, a moving image, a document, a document, and a brochure.

  The object may include a plurality of pieces of feature information that can identify a person. For example, if the object is a photograph, the face image corresponds to feature information that can identify a person. If the object is a mail, the information indicating the sender or the receiver corresponds to the characteristic information that can identify the person. In this specification, the feature information is described as information that can identify a person. However, the feature information is not limited to information that can identify a person. For example, the feature information may be information that can identify any individual such as an animal or a robot.

  The position information includes any information that can identify the position. For example, if the object is a photograph, the above-described object storage unit stores information indicating the shooting location of the photograph in association with the photograph. If the object is a pamphlet, the object storage unit described above stores information indicating the issuance location or a venue such as an event where the pamphlet is distributed in association with the pamphlet. In FIG. 2, the position information is information on a pair of latitude and longitude. This is an example, and the position information may be information indicating a certain position.

  The time information includes any information that can identify the time. For example, if the object is a photograph, the object storage unit described above stores information indicating the photographing time of the photograph in association with the photograph. If the object is a pamphlet, the object storage unit described above stores information indicating the date of issue or the date and time of the event such as an event in which the pamphlet is distributed in association with the pamphlet.

  The user list is a list including two or more user identifiers associated with corresponding object entities. This user identifier is an identifier indicating the person corresponding to the feature information included in the corresponding object. In this specification, the user identifier is described as information that can identify a person. However, the user identifier is not limited to information that can identify a person. For example, the user identifier may be information that can identify any individual such as an animal or a robot.

  The distributed value calculation unit 104 may receive an object identifier, which is information that can identify the object or the object, from another functional unit not shown in FIG. In this case, the variance value calculation unit 104 determines whether or not an object corresponding to the received object or object identifier is stored in the object storage unit. If the variance value calculation unit 104 determines that an object corresponding to the received object or object identifier is stored, the variance value calculation unit 104 reads a user identifier associated with the object. Then, the variance value calculation unit 104 reads the objects associated with all the read user identifiers from the object storage unit.

  The variance value calculation unit 104 calculates the variance value of the position based on the position identified by the position information associated with the object associated with all of the two or more specific user identifiers. Further, the variance value calculation unit 104 calculates the variance value at that time based on the time identified by the time information associated with the object associated with all of the two or more specific user identifiers. .

  For example, the variance value calculation unit 104 may calculate each variance value according to the following formula [Equation 1].

In [Equation 1], t indicates a time dispersion value. p indicates a dispersion value of the position. t _i (i = 1,..., n) indicates the time indicated by the time information associated with the object. P _i (i = 1,..., N) indicates position information associated with the object. This position information is, for example, a value obtained by mapping position information corresponding to an object to a one-dimensional value by a predetermined method.

  [Equation 1] is an exemplification, and the method by which the variance value calculation unit 104 calculates each variance value is not limited to the above formula. For example, when the position information is represented by a set of two values of latitude and longitude, the variance value calculation unit 104 may calculate the variance value of the position based on, for example, the formula [Equation 2].

In [Expression 2], p represents a variance value of the position. p ⁽¹⁾ indicates the variance value of the latitude indicated by the position information associated with the object. p ⁽²⁾ indicates a dispersion value of longitude indicated by position information associated with the object. p _i ⁽¹⁾ (i = 1,..., n) indicates the latitude indicated by the position information associated with the object. p _i ⁽²⁾ (i = 1,..., n) indicates the longitude indicated by the position information associated with the object.

  The variance value calculation unit 104 may weight the predetermined position information associated with the object and calculate the variance value of the position based on the value. For example, the variance value calculation unit 104 may apply a small weight to position information indicating the vicinity of a person's home or work. On the other hand, the variance value calculation unit 104 may apply a large weight to position information indicating a land that is very far from a tourist spot, home, or workplace. For example, the variance value calculation unit 104 may calculate the variance value of the position based on the mathematical formula [Equation 3].

In [Equation 3], p represents a variance value of positions. p _i (i = 1,..., n) indicates position information associated with the object. w _i (i = 1,..., n) depends on whether or not the position information p _i is stored in the variance value calculation unit 104 and is associated with the corresponding user identifier. It is a weight for which a value is determined.

  Similarly, the variance value calculation unit 104 may weight predetermined time information associated with a predetermined object, and calculate a variance value of time based on the value. For example, the variance value calculation unit 104 may apply a small weight to time information indicating working hours or lecture hours, that is, time information indicating daytime on weekdays. On the other hand, the variance value calculation unit 104 may apply a large weight to the time information indicating the night of a holiday or weekday. For each user identifier, the variance value calculation unit 104 associates and stores position information indicating the home or work location of the person identified by the user identifier, and executes the above weighting process based on the information. May be. For example, the variance value calculation unit 104 may calculate the variance value of the time based on the formula of [Equation 4].

In [Equation 4], t represents a variance value of time. t _i (i = 1,..., n) indicates time information associated with the object. _{w i (i = 1, ···} , n) , the time information t _i is, is stored in the variance value calculation unit 104, depending on whether the time information associated with the corresponding user identifier It is a weight for which a value is determined.

  The variance value calculation unit 104 passes the variance value of the position and the variance value of the time calculated based on the two or more specific user identifiers described above and the object associated with the user identifier to the relationship determination unit 105.

=== Relationship Determination Unit 105 ===
The relationship determination unit 105 receives the user identifier, the position variance value, and the time variance value from the variance value calculation unit 104. Then, the relationship determination unit 105 determines a predetermined value between the persons identified by the received user identifier when the position variance value is equal to or greater than the first threshold value and the time variance value is equal to or greater than the second threshold value. Determine that there is a relationship.

  The first threshold value and the second threshold value may be values set in advance by the user of the relationship determination apparatus 100. Alternatively, the relationship determination device 100 may receive information indicating these threshold values from an external device (not shown in FIG. 1), and the relationship determination unit 105 may use the value.

  The predetermined relationship may represent, for example, “related” or “not related”. The predetermined relationship may include a personal relationship such as “just acquaintance”, “acquaintance”, “friend”, “best friend”, “relative”. Alternatively, the predetermined relationship may be expressed using a degree of relationship that is information indicating the degree (or size) of the relationship between the corresponding persons.

  FIG. 3 is a flowchart illustrating an example of an outline of the operation of the relationship determination apparatus 100 according to the first embodiment.

  The variance value calculation unit 104 identifies a user identifier based on information received from an external device (not shown in FIG. 1) (step S101). Then, the variance value calculation unit 104 reads an object associated with at least two specific user identifiers from among the specified user identifiers from an object storage unit (not shown in FIG. 1) (step S102).

  The variance value calculation unit 104 calculates the variance value of the position based on the position identified by the position information associated with the object associated with all of the at least two specific user identifiers. Further, the variance value calculation unit 104 calculates the variance value at that time based on the time identified by the time information associated with the object associated with all of the at least two specific user identifiers described above. (Step S103).

  The relationship determination unit 105 receives from the variance value calculation unit 104 a user identifier, a variance value of position, a variance value of time, and a set of user identifiers used in calculating those values. Then, the relationship determination unit 105 determines a predetermined relationship between the persons identified by the received user identifier when the position variance value is equal to or greater than the first threshold value and the time variance value is equal to or greater than the second threshold value. It is determined that there is (step S104).

  The relationship determination apparatus 100 may repeatedly execute the processes in steps S102 to S104 until all the user identifiers specified in the process of step S101 are selected as “specific user identifiers” in step S102. For example, the relationship determination apparatus 100 performs the processing from step S102 to step S104 until there are no two pairs selected in step S102 in any two pairs included in the user identifier specified in the processing in step S101. It may be executed repeatedly. That is, the relationship determination apparatus 100 selects one arbitrary two set from the user identifiers identified in the process of step S101, and executes the processes of steps S102 to S104 with the selected set as an input. Then, when there is a pair that has not yet been selected from the two sets included in the user identifier specified in the process of step S101, the relationship determination apparatus 100 selects the set and performs the processes of steps S102 to S104. Execute.

  In addition, the relationship determination apparatus 100 may specify a user identifier indicating a relationship source and a user identifier indicating a relationship destination based on information received from an external device (not shown). In this case, the relationship determination apparatus 100 may repeatedly execute the processing from step S102 to step S104 for all combinations of the relationship source user identifier and the relationship destination user identifier.

  The relationship determination apparatus 100 according to the first embodiment reads objects including two or more user identifiers, and specifies position information and time information associated with the objects. Then, the relationship determination apparatus 100 calculates the variance value of the position and the variance value of the time identified by each based on the specified location information and time information. Then, the relationship determination device 100 determines whether the position variance value is greater than or equal to the first threshold value and the time variance value is greater than or equal to the second threshold value. It is determined that there is a predetermined relationship.

  For example, in a case where information that can identify itself is included in a predetermined object before a certain person A intends, in each related technology, there is a predetermined interval between the person A and another person X, Y,. It is determined that there is a relationship (for example, a friend relationship). For example, an object including information that can identify each person during the work may be created between the person A and the person X that have a relationship only on the job. Alternatively, an object including information that can identify the persons A and X without the intention of the person A may be created. In this case, each related technique determines that there is a friendship between the person A and the person X because there is an object including information on the person A and the person X.

  On the other hand, even in such a case, the relationship determination apparatus 100 in the first embodiment calculates a small variance value from the position information and time information associated with the object including the information on the person A and the person X. To do. The relationship determination apparatus 100 determines a predetermined relationship between the person A and the person X (for example, a friend relationship) when the position variance value is equal to or greater than the first threshold value and the time variance value is equal to or greater than the second threshold value. ) Is determined. Therefore, the relationship determination apparatus 100 does not determine that there is a friend relationship between the person A and the person X. That is, the relationship determination apparatus 100 according to the first embodiment can determine a predetermined relationship between persons with high accuracy from an object including information about a plurality of persons.

[First Modification of First Embodiment]
In the first embodiment, the relationship determination device 100 may include the object storage unit described above. FIG. 4 is a diagram illustrating an example in which the relationship determination device 100 according to the first embodiment includes the object storage unit 103.

[Second Modification of First Embodiment]
In the first embodiment, the distributed value calculation unit 104 receives a user identifier, an object, or an object identifier from another functional unit not shown in FIG. Instead, the relationship determination unit 105 may receive a user identifier, an object, or an object identifier from other functional means not shown in FIG. In this case, the relationship determination unit 105 performs the process of the variance value calculation unit 104 in steps S101 and S102 in the operation of the relationship determination apparatus 100 shown in FIG. 3 instead. Then, the relationship determination unit 105 may pass the object read out in step S102 to the variance value calculation unit 104.

[Third Modification of First Embodiment]
In the first embodiment, the relationship determination apparatus 100 includes an object selection unit 106 that selects an object associated with position information or time information used by the variance value calculation unit 104 for calculation of the variance value. Good. FIG. 5 is a block diagram illustrating an example of the configuration of the relationship determination apparatus 100 according to the third modification of the first embodiment.

=== Object Selection Unit 106 ===
The object selection unit 106 selects an object including position information or time information used by the variance value calculation unit 104 for calculation of the variance value.

  Specifically, the object selection unit 106 operates as follows. First, the variance value calculation unit 104 or the relationship determination unit 105 identifies a user identifier, and reads an object associated with at least two specific user identifiers from the identified user identifier from the object storage unit 103. Then, the variance value calculation unit 104 or the relationship determination unit 105 passes the read object to the object selection unit 106. The object selection unit 106 selects a predetermined object from the received objects according to a certain method.

  Examples of the above-described method include the following method. For example, the object selection unit 106 determines the similarity of each object and classifies the similar objects as a group. Then, the object selection unit 106 selects one object from each classified group, and passes the selected object to the variance value calculation unit 104. The variance value calculation unit 104 calculates the above-described variance values based on the object received from the object selection unit 106.

  Further, for example, the object selection unit 106 receives an object identifier from another functional unit (not shown in FIG. 1), and selects an object identified by the received object identifier. Then, the object selection unit 106 passes the selected object to the variance value calculation unit 104. The variance value calculation unit 104 calculates the above-described variance values based on the object received from the object selection unit 106.

  In the relationship determination apparatus 100 according to the third modification of the first embodiment, the object selection unit 106 selects an appropriate object for calculating a variance value. Therefore, even when there are a large number of objects associated with information indicating a specific position and place by the continuous shooting function, for example, the relationship determination apparatus 100 eliminates such overlapping of similar objects, thereby improving accuracy. In addition, it is possible to reduce the calculation amount.

  Further, the relationship determination device 100 according to the third modification of the first embodiment calculates each variance value based on an object identified by an object identifier received from an external device (not shown). Therefore, for example, the relationship determination apparatus 100 can calculate each variance value using an object selected by the user as a population, and can determine the relationship between persons based on each variance value.

[Second Embodiment]
FIG. 6 is a block diagram showing the configuration of the relationship determination system 20 according to the second embodiment of the present invention. Referring to FIG. 6, the relationship determination system 20 includes a relationship determination device 200 and a user terminal 211. According to FIG. 6, the relationship determination system 20 includes one user terminal 211, but the number of user terminals 211 included in the relationship determination system 20 is not limited thereto. For example, in the following description, the relationship determination system 20 may include a plurality of user terminals 211. Hereinafter, the configuration of the relationship determination apparatus 200 will be described.

  FIG. 7 is a block diagram illustrating a configuration of the relationship determination device 200. Referring to FIG. 7, the relationship determination apparatus 200 includes an object reception unit 201, an object related person acquisition unit 202, an object storage unit 103, a variance value calculation unit 104, and a relationship determination unit 205. The configuration of the object storage unit 103 is the same as the configuration of the object storage unit 103 in the first modification of the first embodiment. The configuration of the variance value calculation unit 104 is the same as the configuration of the variance value calculation unit 104 in the first embodiment.

=== Object Receiving Unit 201 ===
The object reception unit 201 receives from the user terminal 211 an object including feature information that is information that can identify a person, position information associated with the object, and time information.

=== Object Related Person Acquisition Unit 202 ===
The object related person acquisition unit 202 acquires a user identifier corresponding to the feature information from the feature information included in the object received by the object reception unit 201.

  For example, when the object is a photograph, the object-related person acquisition unit 202 detects a face image by performing image recognition processing, and identifies a person corresponding to the face image. Here, the face image corresponds to the above-described feature information.

  In this case, the object related person acquisition unit 202 preferably stores the face image and a user identifier that can identify a person in association with each other. Alternatively, the object-related person acquisition unit 202 is connected to a face ID storage unit that stores a face image and a user identifier that can identify a person in association with each other, and reads the user identifier from the face ID storage unit based on the face image. May be. FIG. 8 is a diagram illustrating an example of information stored in the face ID storage unit. Referring to FIG. 8, the face ID storage unit stores an object entity and a user identifier in association with each other. The user identifier is a user identifier that can identify a person. The object entity is data of the face image of the person identified by the corresponding user identifier.

  When the object receiving unit 201 receives an object, the object related person acquisition unit 202 may transmit an input request that is information for requesting input of a user identifier to the user terminal 211 described above. In this case, the object related person acquisition unit 202 receives the user identifier transmitted from the user terminal 211 in response to the input request.

  If the object is a paper, the object-related person acquisition unit 202 detects information on the author name and information indicating the affiliation of the author by performing character recognition processing, natural language analysis processing, and the like. Then, the object-related person acquisition unit 202 specifies a person corresponding to the author name. Here, the information on the author name and the information indicating the affiliation of the author correspond to the above-described feature information.

  When the object is a pamphlet, the object-related person acquisition unit 202 detects the name of the performer of the event related to the pamphlet and the e-mail address of the performer by performing character recognition processing, natural language analysis processing, and the like. . Then, the object related person acquisition unit 202 specifies a person corresponding to the performer. Here, the information of the performer and the e-mail address of the performer correspond to the above-described feature information.

  Each example of the above-described feature information is merely an example, and the feature information is not limited to each information. The feature information may be information included in the object and capable of specifying a certain person.

  The object related person acquisition unit 202 associates the user identifier acquired by any of the above-described methods, the corresponding object, and the position information and time information associated with the object in the object storage unit 103. Remember. At this time, the object-related person acquisition unit 202 may generate an object identifier that can uniquely identify the object. Furthermore, the object related person acquisition unit 202 may store the object identifier in the object storage unit 103 in association with each corresponding object.

=== Relationship Determination Unit 205 ===
The relationship determination unit 205 receives the user identifier, the position variance value, and the time variance value from the variance value calculation unit 104. The relationship determination unit 205 identifies the person identified by the user identifier received by the relationship determination unit 205 when the position variance value is equal to or greater than the first threshold value and the time variance value is equal to or greater than the second threshold value. It is determined that there is a predetermined relationship between them. The first threshold value and the second threshold value may be determined by the same method as in the first embodiment.

  In addition, the relationship determination unit 205 determines that there is a limited relationship between the persons identified by the above-described user identifier received by the relationship determination unit 205 when predetermined conditions exemplified below are satisfied.

  A limited relationship is any human relationship that appears when a restriction is placed on at least one of position and time. For example, the limited relationships include “work relationships”, “colleagues”, “business partners”, “circle friends”, “students with the same lessons”, “school classmates”, “seniors”, “juniors”, and the like.

  For example, the relationship determination unit 205 may determine whether the variance value at the position calculated by the variance value calculation unit 104 is less than the first threshold value and the variance value at the time is less than the second threshold value. If it is satisfied, it is determined that there is a limited relationship between the aforementioned persons. FIG. 9 is a diagram illustrating an example of a determination result in which the relationship determination unit 205 determines the relationship based on each variance value. In FIG. 9, x is a second threshold value. Y is the first threshold value.

  Referring to FIG. 9, the relationship determination unit 205 determines that a predetermined relationship D exists between the corresponding persons when the position variance value p is greater than or equal to the threshold value y and the time variance value t is greater than or equal to the threshold value x. Judge that there is. Further, the relationship determination unit 205 determines that there is a limited relationship C between the corresponding persons when the position variance value p is greater than or equal to the threshold value y and the time variance value t is less than the threshold value x. . The relationship determination unit 205 determines that there is a limited relationship B between the corresponding persons when the position variance value p is less than the threshold value y and the time variance value t is greater than or equal to the threshold value x. . The relationship determination unit 205 determines that there is a limited relationship A between the corresponding persons when the position variance value p is less than the threshold value y and the time variance value t is less than the threshold value x. . The relationship determination unit 205 may determine that this limited relationship A is a “particularly limited relationship” and specify it as a relationship different from the relationship B or C described above. A “particularly limited relationship” is any human relationship that appears as a result of certain restrictions on position and time.

  The relationship determination unit 205 identifies the number of objects used when the variance value calculation unit 104 calculates each variance value, and determines whether a predetermined value is set between persons based on whether the number is equal to or greater than a predetermined threshold. It may be determined whether there is a relationship or whether there is a limited relationship. FIG. 10 is a diagram illustrating an example of a determination result in which the relationship determination unit 205 determines the relationship based on each variance value. In FIG. 10, m is a predetermined threshold value. In FIG. 10, A to D correspond to A to D in FIG. 9, respectively.

  Referring to FIG. 10, the relationship determination unit 205 identifies one of the relationships A to D based on the position variance value and the time variance value, and the variance value calculation unit 104 further determines each variance value. The relationship between A and D is specifically specified based on the number of objects used when calculating. For example, the relationship determination unit 205 determines that there is a relationship of D based on the variance value of the position and the variance value of the time, and if the number of objects is equal to or more than m, a close friend relationship is established between the persons. Judge that there is. Also, for example, the relationship determination unit 205 determines that there is a relationship of D based on the variance value of the position and the variance value of the time, and if the number of objects is less than m, the friend relationship between the persons Judge that there is.

  The relationship determination unit 205 transmits information indicating the determined relationship to an external device such as a user terminal. Specifically, the relationship determination unit 205 includes a set of user identifiers, information indicating a relationship between persons identified by the user identifiers included in the set, and a position used when determining the relationship. The information including the variance value and the time variance value is transmitted.

  The relationship determination unit 205 may specify the degree of relationship, which is information indicating the degree (or size) of the relationship between corresponding persons, as information indicating the relationship. For example, the relationship determination unit 205 may specify the linear sum of the respective variance values as the relationship degree as in the following [Equation 5].

  In [Expression 5], R indicates the degree of relationship. t indicates a time dispersion value. p indicates a dispersion value of the position. α and β represent arbitrary real numbers. α and β may be predetermined values.

  Next, the configuration of the user terminal 211 will be described.

  The user terminal 211 transmits an object including feature information, which is information that can identify a person, position information associated with the object, and time information to the relationship determination apparatus 200.

  In addition, the user terminal 211 transmits a user identifier, which is information that can identify a person, to the relationship determination apparatus 200. This user identifier is a user identifier that can identify a person whose relationship is to be examined. The user terminal 211 may transmit an object identifier that can identify the object or the object to the relationship determination apparatus 200 instead of transmitting the user identifier.

  In addition, the user terminal 211 is used when determining a relationship between a set of user identifiers, information indicating a relationship between persons identified by the user identifier included in the set, and the relationship from the relationship determination device 200. The information including the variance value of the position and the variance value of the time is received. Then, the user terminal 211 outputs each received information to an output device such as a display.

  FIG. 11 is an example of information output by the user terminal 211. FIG. 11 shows information indicating the relationship between a specific person and the user at each time indicated on the horizontal axis for each person corresponding to the user identifier received by the user terminal 211. A specific person is a user of the user terminal 211, for example. Alternatively, the user of the user terminal 211 may designate one specific person among the persons identified by the user identifier received by the user terminal 211. The information indicating the relationship in FIG. 11 is the aforementioned degree of relationship. In FIG. 11, the horizontal axis is shown in units of one day, but this may be in units of months or years. The horizontal axis may display time without any particular unit.

  Referring to FIG. 11, based on information output from the user terminal 211, a certain user can visually grasp what action is being taken against other users related to the user with respect to time changes. . In addition, a certain user can grasp the change in temporal human relationship of the actions of other related users. For example, when a certain user is a parent and another user is a friend related to the child of the parent, the parent can easily grasp the temporal change in the human relationship of the child.

  FIG. 12 is another example of information output from the user terminal 211. FIG. 12 is information obtained by plotting a position variance value and a time variance value calculated based on an object including a specific person for each person corresponding to the user identifier received by the user terminal 211. Although not shown in FIG. 12, the plotted points may include information indicating the number of objects used when the variance value calculation unit 104 calculates each variance value. In this case, the relationship determination unit 205 transmits to the user terminal 211 the number of objects used to calculate each variance value that is the basis of the relationship when transmitting the relationship to the user terminal 211.

  Here, the specific person is a user of the user terminal 211, for example. Alternatively, the user of the user terminal 211 may designate one specific person among the persons identified by the user identifier received by the user terminal 211.

  FIG. 12 includes information indicating the relationship between the specific person described above and the person corresponding to the user identifier received by the user terminal 211 for each person. Specifically, in FIG. 12, information indicating that there is a predetermined relationship with the persons H and I is associated. The user terminal 211 identifies and outputs the boundary line of each category so that the plots of the user identifiers associated with each person and having the same information indicating the relationship are included in the common category. In FIG. 12, the boundary lines of t ≧ x and p ≧ y correspond to the boundary lines of each category. Here, t is a time dispersion value. p is the variance value of the position. x is a second threshold value. y is the first threshold value. In FIG. 12, this means that the person identified by the user identifier corresponding to the information plotted in the region of t ≧ x and p ≧ y has a predetermined relationship with the specific person.

  FIG. 13 is another example of information output from the user terminal 211. FIG. 13 includes the same information as FIG. Description of information common to FIG. 12 is omitted.

  FIG. 13 includes information indicating the relationship between the specific person described above and the person corresponding to the user identifier received by the user terminal 211. Specifically, in FIG. 13, information indicating that there is a limited relationship with persons A and C is associated. Further, information indicating that there is a particularly limited relationship with the persons B and D is associated. Further, information indicating that there is a limited relationship with the persons E, F, and G is associated. Also, information indicating that there is a predetermined relationship with the persons H and I is associated. The user terminal 211 identifies and outputs the boundary line of each category so that the plots of the user identifiers associated with each person and having the same information indicating the relationship are included in the common category.

  In FIG. 13, the boundary lines of t = x (0 ≦ t ≦ x) and p = y (0 ≦ p ≦ y) correspond to information indicating the relationship. In FIG. 13, it means that the person identified by the user identifier corresponding to the information plotted in the region of t ≧ x and p ≧ y has a predetermined relationship with the specific person. Further, in FIG. 13, it means that the person identified by the user identifier corresponding to the information plotted in the region of 0 ≦ t <x and p ≧ y has a limited relationship with the specific person described above. To do. Further, in FIG. 13, it means that the person identified by the user identifier corresponding to the information plotted in the region of t ≧ x and 0 ≦ p <y has a limited relationship with the specific person described above. To do. Furthermore, in FIG. 13, the person identified by the user identifier corresponding to the information plotted in the areas 0 ≦ t <x and 0 ≦ p <y has a particularly limited relationship with the specific person described above. It means that.

  FIG. 14 is a diagram illustrating an example of an outline of the operation of the relationship determination system 20 in the second embodiment.

  The user terminal 211 transmits an object including feature information, position information associated with the object, and time information to the relationship determination apparatus 200 (step S201). The object reception unit 201 receives an object including feature information, position information associated with the object, and time information (step S202).

  The object related person obtaining unit 202 obtains a user identifier corresponding to the feature information from the feature information included in the object received by the object receiving unit 201 by a predetermined method (step S203).

  The object related person acquisition unit 202 stores the user identifier acquired by a predetermined method, the corresponding object, and the position information and time information associated with the object in the object storage unit 103 in association with each other ( Step S204).

  The user terminal 211 transmits a user identifier that can identify a person whose relationship is to be checked to the relationship determination apparatus 200 (step S205).

  The variance value calculation unit 104 receives a user identifier from the user terminal 211. Then, the variance value calculation unit 104 reads an object associated with at least two specific user identifiers from the received user identifiers from the object storage unit 103 (step S206).

  The variance value calculation unit 104 calculates the variance value of the position based on the position identified by the position information associated with the object associated with all of the at least two specific user identifiers. Further, the variance value calculation unit 104 calculates the variance value at that time based on the time identified by the time information associated with the object associated with all of the at least two specific user identifiers described above. (Step S207).

  The relationship determination unit 205 receives the position variance value calculated by the variance value calculation unit 104, the time variance value, and a set of user identifiers used in calculating these values. Then, the relationship determination unit 205 specifies a relationship between persons that can be identified by the received user identifier based on each variance value, and generates information indicating the relationship (step S208). The relationship determination unit 205 includes a set of user identifiers, information indicating the relationship between persons identified by the user identifiers included in the set, and a variance value and time of a position used when determining the relationship The information including the variance value is transmitted (step S209).

  The user terminal 211 receives a set of user identifiers from the relationship determination apparatus 200, information indicating the relationship between persons identified by the user identifier included in the set, and the position used when determining the relationship. Information including a variance value and a variance value of time is received. Then, the user terminal 211 outputs each received information to an output device such as a display (step S210).

  The relationship determination apparatus 200 repeatedly executes the processes from step S206 to step S208 until all the user identifiers transmitted from the user terminal 211 in the process of step S205 are selected as “specific user identifiers” in step S206. May be. For example, the relationship determination apparatus 200 performs steps S206 through S206 until there are no two pairs selected in step S206 in any two pairs included in the user identifier transmitted from the user terminal 211 in the process of step S205. You may repeat and process step S208. That is, the relationship determination apparatus 200 selects one arbitrary two set from the user identifiers transmitted from the user terminal 211 in the process of step S205, and performs the processes of steps S206 to S208 with the selected set as an input. Execute. If there is a pair that has not yet been selected from the two sets included in the user identifier transmitted from the user terminal 211 in the process of step S205, the relationship determination apparatus 200 selects the set, and steps S206 to S206 The process of step S208 is executed.

  In addition, the relationship determination apparatus 200 may receive a user identifier indicating a relationship source and a user identifier indicating a relationship destination in the process of step S205. In this case, the relationship determination apparatus 200 may repeatedly execute the processing from step S206 to step S208 for all combinations of the relationship source user identifier and the relationship destination user identifier.

  According to the relationship determination system 20 in the second embodiment, the user terminal 211 transmits to the relationship determination device 200 a user identifier that can identify a person whose relationship is to be checked. Then, an object associated with two or more specific user identifiers among the user identifiers received by the relationship determination apparatus 200 is read from the object storage unit 103. And the positional infomation and time information matched with the object which the relationship determination apparatus 200 read are specified. Then, the relationship determination apparatus 200 calculates the variance value of the position and the variance value of the time identified based on the specified location information and time information. And the relationship determination apparatus 200 produces | generates the information which shows the relationship between applicable persons based on the calculated dispersion | distribution value.

  For example, when a certain person A unintentionally includes information that can identify himself / herself in a predetermined object, each related technique uses a predetermined amount between the person A and another person X, Y,. It is determined that there is a relationship (for example, a friend relationship). For example, an object including information that can identify each person during the work may be created between the person A and the person X that have a relationship only on the job. Alternatively, an object including information that can identify the persons A and X without the intention of the person A may be created. In this case, each related technique determines that there is a friendship between the person A and the person X because there is an object including information on the person A and the person X.

  On the other hand, even in such a case, the relationship determination apparatus 100 according to the second embodiment calculates a small variance value from the position information and time information associated with the object including information about the person A and the person X. To do. The relationship determination apparatus 100 determines a predetermined relationship between the person A and the person X (for example, a friend relationship) when the position variance value is equal to or greater than the first threshold value and the time variance value is equal to or greater than the second threshold value. ) Is determined. Therefore, the relationship determination apparatus 200 does not determine that there is a friendship between the person A and the person X. Instead, the relationship determination apparatus 200 determines that there is a limited relationship between the person A and the person X that is different from the predetermined relationship, for example, a social relationship only at work.

  That is, the relationship determination apparatus 200 according to the second embodiment can determine a predetermined relationship between persons with high accuracy from an object including information about a plurality of persons. Furthermore, the relationship determination apparatus 200 can determine that there is a limited relationship between the corresponding persons when there is some relationship in the position or time associated with the object including information regarding a plurality of persons. The case where there is a relationship between the position or time means that at least one of the position variance value is less than the first threshold value and the time variance value is less than the second threshold value is satisfied. is there.

[First Modification of Second Embodiment]
In the second embodiment, the user terminal 211 may correct a boundary line of a category including a user identifier indicating a common relationship based on information input from the user. FIG. 15 is a diagram illustrating an example of an outline in which the user terminal 211 corrects the boundary line of the category based on the information of the user input 1000 input from the person X. Referring to FIG. 15, the person included in the category “Circle” is changed from “A, C” to “A, B, C, D” based on the user input 1000.

  When the user terminal 211 corrects the boundary line of the category, the user terminal 211 transmits information indicating that to the relationship determination apparatus 200. For example, the user terminal 211 transmits information indicating that the person “A, B, C, D” has the same relationship as the person X to the relationship determination apparatus 200. When the relationship determination apparatus 200 receives the above-described information, the relationship determination unit 205 changes, for example, at least one of the first threshold and the second threshold so that the person X and the persons A, B, C, and D Adjust to determine that they have the same relationship.

  Specifically, the relationship determination unit 205 receives information indicating that the person “A, B, C, D” has the same relationship as the person X, for example. Specifically, this information is a set of a set of a user identifier indicating the person X and a user identifier indicating each of the persons A, B, C, and D. When the variance value calculation unit 104 receives a set of user identifier sets from the relationship determination unit 205, the variance value calculation unit 104 reads objects associated with all the user identifiers included in each set. Then, the variance value calculation unit 104 calculates the variance value of the position and the variance value of the time based on the object read for each set of user identifiers. The variance value calculation unit 104 passes each calculated variance value to the relationship determination unit 205. The relationship determination unit 205 determines that the person X and the persons A, B, C, and D have the same relationship based on each received variance value so as to determine the same relationship between the first threshold and the second threshold. At least one of the threshold values is changed.

  The user terminal 211 may receive information indicating a category from the user for each person identified by the received user identifier. Then, the user terminal 211 corrects the boundary line of the category including the user identifier indicating the common relationship so that the user identifiers having the common information indicating the received category indicate the same relationship.

  The user terminal 211 may receive the name of the category together with information indicating the category, and output the name of the category together with the category.

  For example, the user terminal 211 receives address book information including information on a plurality of users from the user, and includes a user identifier indicating a common relationship based on information on groups to which the users included in the address book information respectively belong. Correct the boundaries of categories Specifically, the user terminal 211 is configured such that the category boundary including user identifiers indicating a common relationship so that user identifiers identifying users belonging to the same group included in the received address book information indicate the same relationship. Correct the line.

  Also, the user terminal 211 outputs the name of each group included in the address book information including information on a plurality of users in association with each category corresponding to the user identifier that can identify the user included in the group. Also good.

  The relationship determination system 20 according to the first modification of the second embodiment is configured so that, for example, a relationship between a new person who is not registered in the address book and the owner of the address book is a person registered in the address book. And can be identified based on the relationship.

  For example, it is assumed that a category as shown in FIG. 17 is defined based on user information stored in the address book 1001 as shown in FIG. In this case, for example, the relationship determination unit 205 determines the relationship between the person Z who is not registered in the address book and a specific person who is the owner of this address book, as shown in FIG. Then, it can be seen that the person Z is included in a category corresponding to a group (group name “circle”) included in the address book. In this case, the user terminal 211 can output a message that prompts the person terminal 211 to be registered in the “circle” of the address book, for example, as shown in FIG.

  Therefore, the relationship determination system 20 in the first modification of the second embodiment specifies the relationship between persons determined by the relationship determination system 20 with higher accuracy based on information owned by a predetermined user. Can do.

[Third embodiment]
FIG. 20 is a block diagram illustrating a configuration of the relationship determination system 30 according to the third embodiment. Referring to FIG. 20, the relationship determination system 30 includes a relationship determination device 300 and a user terminal 211. Similar to the relationship determination system 20 in the second embodiment, the number of user terminals 211 provided in the relationship determination system 30 is not limited to one. For example, in the following description, the relationship determination system 30 may include a plurality of user terminals 211. Hereinafter, the configuration of the relationship determination apparatus 300 will be described.

  FIG. 21 is a block diagram illustrating a configuration of the relationship determination device 300. Referring to FIG. 21, the relationship determination apparatus 300 includes an object reception unit 201, an object related person acquisition unit 202, an object storage unit 103, a variance value calculation unit 304, a relationship determination unit 305, and a live activity line storage. A unit 307 and a raw activity line divergence degree calculation unit 308. The configuration of the object storage unit 103 is the same as the configuration of the object storage unit 103 in the first modification of the first embodiment. The configuration of the object reception unit 201 is the same as the configuration of the object reception unit 201 in the second embodiment. The object related person acquisition unit 202 has the same configuration as that of the object related person acquisition unit 202 in the second embodiment.

=== Live Activity Line Storage Unit 307 ===
The raw activity line storage unit 307 stores a user identifier that can identify a person and raw activity line information that indicates the corresponding person's raw activity line in association with each other. FIG. 22 is a diagram illustrating an example of information stored in the live activity line storage unit 307.

  A life activity line is a set of positions or routes where a person acts in daily life. The live activity line information is information indicating a live activity line that is a set of positions or routes. For example, the raw activity line information may be a set including a plurality of pairs of latitude and longitude, or may be information including information indicating a certain starting point and a plurality of vectors. The live activity line information may include information indicating time. For example, the raw activity line information may be a set including a plurality of sets of information indicating latitude, longitude, and time, a set of information indicating information indicating a certain starting point and a certain time, a plurality of vectors, It may be information including a pair with information indicating time.

  The live activity line information may be information specified based on at least one of position information and time information included in a life log collected by a communication carrier. Alternatively, the relationship determination device 300 may receive information indicating a position from a communication device used by each person and generate live activity line information based on the received information. For example, the relationship determination device 300 periodically collects information on each person's live activity line based on a GPS (Global Positioning System) function provided in the communication device, and generates live activity line information based on the information. Also good.

  The live activity line may be a set of positions or routes where a person frequently acts in daily life. In this case, the relationship determination apparatus 300 saves the live activity line as the live activity line information as the live activity line information when the information indicating the position or the route included in the live activity line information is a predetermined number or more. You may memorize | store in the part 307.

=== Live Activity Line Deviation Calculation Unit 308 ===
When the variance value calculation unit 304 reads an object associated with a specific user identifier, the live activity line divergence calculation unit 308 performs the following processing for each object. That is, the live activity line divergence calculating unit 308 receives the specific user identifier and the position information associated with the object from the variance value calculating unit 304. Then, the live activity line divergence calculating unit 308 reads the live activity line information associated with the user identifier from the live activity line storage unit 307 for each specific user identifier described above. The live activity line divergence calculating unit 308 calculates the shortest distance between the position specified by the received position information and the route specified by the read live activity line information. The live activity line divergence calculating unit 308 identifies the live activity line divergence based on the calculated shortest distance.

  FIG. 23 is a diagram illustrating an example of the raw activity line divergence degree specified by the raw activity line divergence degree calculation unit 308 based on the shortest distance. Referring to FIG. 23, when the shortest distance is less than 3 kilometers, the divergence degree is specified as 1. When the shortest distance is 3 km or more and less than 10 km, the divergence degree is specified as 2. When the shortest distance is 10 km or more and less than 50 km, the divergence degree is specified as 3. When the shortest distance is 50 kilometers or more, the divergence degree is specified as 4.

  The raw activity line divergence calculation unit 308 passes the calculated raw activity line divergence degree to the variance value calculation unit 304 together with the specific user identifier described above. The raw activity line divergence calculating unit 308 may pass the raw activity line divergence degree and the specific user identifier to the variance value calculating unit 304 together with the number of objects described above.

=== Dispersion Value Calculation Unit 304 ===
The variance value calculation unit 304 receives a user identifier from the user terminal 211. Then, the variance value calculation unit 304 reads an object associated with at least two specific user identifiers from the received user identifiers from the object storage unit 103. This operation is the same as the operation of the variance value calculation unit 104 in the first embodiment.

  The variance value calculation unit 304 passes the position information associated with each of the read objects and the above-described at least two specific user identifiers to the live activity line divergence calculation unit 308. The variance value calculation unit 304 receives the specific user identifier and the live activity line divergence.

  The variance value calculation unit 304 calculates the average value of the live activity line divergence degrees corresponding to the objects associated with all the at least two specific user identifiers based on the received live activity line divergence degree.

  The variance value calculation unit 304 calculates the variance value of the position based on the position identified by the position information associated with the object associated with all of the at least two specific user identifiers described above. To do. Further, the variance value calculation unit 304 calculates the variance value at that time based on the time identified by the time information associated with the object associated with all of the above-described at least two specific user identifiers. . This operation is the same as the operation of the variance value calculation unit 104 in the first embodiment.

  24, the variance value calculation unit 304 calculates the variance value of the position, the variance value of the time, and the average value of the live activity line divergence degree based on the objects associated with the user identifiers of the person M and the person N. It is a figure which shows an example of a result. Referring to FIG. 24, the time variance value 9.96443 is calculated for eight objects of picture003 to picture010. In FIG. 24, the position variance value is expressed by a latitude variance value and a longitude variance value. Then, the latitude dispersion value 0.02605 is calculated for eight objects of picture003 to picture010. Similarly, a longitude dispersion value of 0.01893 is calculated. Moreover, the average value 1.375 of the divergence level of the live activity line is calculated.

  The variance value calculation unit 304 creates a new activity based on the live activity line divergence received from the live activity line divergence calculation unit 308 and the time information associated with the object from which the live activity line divergence is calculated. The degree of deviation may be calculated. FIG. 25 is a diagram illustrating an example of a new divergence degree calculated by the variance value calculation unit 304. Referring to FIG. 25, the variance value calculation unit 304 calculates the degree of deviation when the time information associated with the object indicates “holiday”, and the time information associated with the object. Is calculated so that the degree of divergence decreases when “Weekdays” is indicated.

  The variance value calculation unit 304 may obtain an average value of the new divergence degree instead of calculating the average value of the above-mentioned live activity line divergence degree.

  The variance value calculation unit 304 passes the variance value of the position, the variance value of the time, and the average value of the live activity line divergence degree to the relationship determination unit 305 in association with the corresponding user identifier.

=== Relationship determination unit 305 ===
The relationship determination unit 305 receives the position variance value, the time variance value, and the average value of the raw activity line divergence values calculated by the variance value calculation unit 304 together with the user identifiers corresponding to these values.

  The relationship determination unit 305 determines that there is a predetermined relationship between the persons identified by the received user identifier when the following conditions are satisfied. The first condition is that the variance value of the position received by the relationship determination unit 305 together with the user identifier is equal to or greater than the first threshold value, and the variance value of the time is equal to or greater than the second threshold value. The second condition is that the raw activity line divergence received together with the aforementioned user identifier is equal to or greater than a predetermined threshold.

  The relationship determination unit 305 may specify the degree of relationship, which is information indicating the degree (or size) of the relationship between corresponding persons, as information indicating the relationship. For example, the relationship determination unit 305 may identify the linear sum of the respective variance values as the relationship degree as in the following [Equation 6].

  In [Expression 6], R represents the degree of relationship. t indicates a time dispersion value. p indicates a dispersion value of the position. l represents the average value of the deviation of the lifeline. α, β, and γ represent arbitrary real numbers. α, β, and γ may be predetermined values.

  FIG. 26 is a flowchart illustrating an example of the operation of the relationship determination system 30 according to the third embodiment. In FIG. 26, the operations in steps S301 through S306 are the same as the operations in steps S201 through S206 in FIG. 14, respectively. Therefore, the description is omitted.

  The variance value calculation unit 304 passes the position information associated with each read object and the user identifier associated with the object to the live activity line divergence calculation unit 308 (step S307).

  The raw activity line divergence calculating unit 308 receives the above-described specific user identifier and position information associated with the object from the variance value calculating unit 304. Then, the live activity line divergence calculation unit 308 reads, for each specific user identifier described above, the live activity line information associated with the user identifier from the live activity line storage unit 307 (step S308).

  Then, the live activity line divergence calculating unit 308 calculates the shortest distance between the position specified by the received position information and the route specified by the read live activity line information (step S309). Then, the live activity line divergence calculation unit 308 specifies the live activity line divergence based on the calculated shortest distance (step S310).

  The raw activity line divergence calculation unit 308 passes the calculated raw activity line divergence degree to the variance value calculation unit 304 together with the specific user identifier described above.

  Based on the position identified by the position information associated with the object associated with all of the at least two specific user identifiers selected in step S306, the variance value calculation unit 304 Calculate the variance value of the position. Further, the variance value calculation unit 304 calculates the variance value at that time based on the time identified by the time information associated with the object associated with all of the above-described at least two specific user identifiers. (Step S311).

  Further, the variance value calculation unit 304 calculates the average value of the live activity line divergence degrees corresponding to the objects associated with all of the at least two specific user identifiers based on the received live activity line divergence degrees. (Step S312). The variance value calculation unit 304 provides the relationship determination unit 305 with the location variance value, the time variance value, the average value of the divergence level of the live activity line, and the set of user identifiers used in calculating these values. hand over.

  The relationship determination unit 305 includes a set of user identifiers used in calculating the variance value of the position calculated by the variance value calculation unit 304, the variance value of the time, the average value of the live activity line divergence, and those values. Receive. Then, the relationship determination unit 305 identifies the relationship between the corresponding persons based on each variance value and the average value of the live activity line divergence, and generates information indicating the relationship (step S313). The relationship determination unit 305 includes a set of user identifiers, information indicating the relationship between persons identified by the user identifiers included in the set, and a variance value and time of a position used when determining the relationship. The information including the variance value is transmitted (step S314).

  The user terminal 211 receives a set of user identifiers from the relationship determination device 300, information indicating the relationship between persons identified by the user identifier included in the set, and the position used when determining the relationship. Information including a variance value and a variance value of time is received. Then, the user terminal 211 outputs each received information to an output device such as a display (step S315).

  The relationship determination apparatus 300 repeats the processes from step S306 to step S313 until all the user identifiers transmitted from the user terminal 211 in the process of step S305 are selected as “specific user identifiers” in step S306. May be. For example, the relationship determination apparatus 300 performs steps S306 through S306 until there are no two pairs that are not selected in step S306 among any two pairs included in the user identifier transmitted from the user terminal 211 in the process of step S305. The process in step S313 may be repeated. That is, the relationship determination apparatus 300 selects one arbitrary pair from the user identifiers transmitted from the user terminal 211 in the process of step S305, and performs the processes of steps S306 to S313 using the selected pair as an input. Execute. If there is a pair that has not yet been selected from the two sets included in the user identifier transmitted from the user terminal 211 in the process of step S305, the relationship determination apparatus 300 selects the set, and steps S306 to S306 are performed. The process of step S313 is executed.

  In addition, the relationship determination apparatus 300 may receive a user identifier indicating a relationship source and a user identifier indicating a relationship destination in the process of step S305. In this case, the relationship determination apparatus 300 may repeatedly execute the processing from step S306 to step S313 for all combinations of the relationship source user identifier and the relationship destination user identifier.

  The relationship determination system 30 according to the third embodiment determines a relationship between persons based on live activity line information indicating a live activity line that is a set of positions or routes where a person has acted in daily life. To do. Therefore, the relationship determination system 30 according to the third embodiment can customize the determination criterion of the relationship between persons for each person, and therefore can determine the relationship between persons with higher accuracy.

[Fourth embodiment]
FIG. 27 is a block diagram illustrating a configuration of the relationship determination system 40 in the fourth embodiment. Referring to FIG. 27, the relationship determination system 40 includes a relationship determination device 400 and a user terminal 411. Similar to the relationship determination system 20 in the second embodiment, the number of user terminals 411 included in the relationship determination system 40 is not limited to one. For example, in the following description, the relationship determination system 40 may include a plurality of user terminals 411. Hereinafter, the configuration of the relationship determination apparatus 400 will be described.

  FIG. 28 is a block diagram illustrating a configuration of the relationship determination apparatus 400. Referring to FIG. 28, the relationship determination device 400 includes an object reception unit 201, an object related person acquisition unit 202, an object storage unit 103, a variance value calculation unit 404, a relationship determination unit 205, and a friendship degree calculation. Part 409. The configuration of the object storage unit 103 is the same as the configuration of the object storage unit 103 in the first modification of the first embodiment. The configuration of the object reception unit 201 is the same as the configuration of the object reception unit 201 in the second embodiment. The object related person acquisition unit 202 has the same configuration as that of the object related person acquisition unit 202 in the second embodiment. The configuration of the relationship determination unit 205 is the same as the configuration of the relationship determination unit 205 in the second embodiment.

=== Friendship calculator 409 ===
The friendship degree calculation unit 409 executes the following processing when the object related person acquisition unit 202 newly stores an object in the object storage unit 103. That is, the friendship degree calculation unit 409 receives from the object related person acquisition unit 202 a user identifier associated with the new object and an object identifier that can identify the new object. Then, the friendship degree calculation unit 409 passes the received user identifier and object identifier to the distributed value calculation unit 404.

  The friendship degree calculation unit 409 obtains the variance value at the first position, the variance value at the first time, and the values calculated based on the objects excluding the above-mentioned new object from the variance value calculation unit 404. Receive a set of user identifiers used in the calculation. Also, the friendship degree calculation unit 409 calculates the variance value at the second position, the variance value at the second time, and those values calculated from the variance value calculation unit 404 based on the object to which the new object is added. And a set of user identifiers used in calculating.

  The friendship degree calculation unit 409 calculates the difference between the variance value at the first position and the variance value at the second position, and the difference between the variance value at the first time and the variance value at the second time. Then, the friendship degree calculation unit 409 calculates a friendship degree that indicates a change in the relationship between persons that can be identified by the user identifier received together with each variance value that is the basis of the difference based on the calculated difference.

  The friendship degree is information indicating a change in the relationship between persons. In the present embodiment, the friendship degree is defined as information that increases as the predetermined relationship increases. For example, when a predetermined person goes out to various places together at various times to take pictures, a predetermined relationship between the predetermined persons increases. Thereby, it is judged that a friend degree also becomes high.

  For example, the friendship degree calculation unit 409 may specify the linear sum of each difference as the friendship degree as in the following [Equation 7].

  In [Expression 7], F indicates the degree of friendship. Δt indicates a difference in time dispersion values. Δp represents the difference in the variance values of the positions. α and β represent arbitrary real numbers. α and β may be predetermined values.

  The friendship degree calculation unit 409 transmits to the user terminal 411 a set of user identifiers and a friendship degree between persons who can be identified by those user identifiers.

=== Dispersion Value Calculation Unit 404 ===
The variance value calculation unit 404 receives a user identifier from the user terminal 411. Then, the distributed value calculation unit 404 obtains an object associated with two or more specific user identifiers among the received user identifiers, a specific user identifier associated with the objects, position information, and time information. Read from the object storage unit 103.

  The variance value calculation unit 404 calculates the variance value of the position based on the position identified by the position information associated with the read object. Further, the variance value calculation unit 404 calculates the variance value at that time based on the time identified by the time information associated with the read object.

  The variance value calculation unit 404 includes a user identifier, a location variance value calculated based on an object associated with the user identifier, a time variance value, and a set of user identifiers used in calculating those values. To the relationship determination unit 205.

  The above operation is the same as the operation of the variance value calculation unit 104 in the second embodiment.

  The variance value calculation unit 404 receives a user identifier and an object identifier from the friend degree calculation unit 409. Then, the variance value calculation unit 404 reads an object, position information, and time information associated with all of two or more specific user identifiers included in the received user identifier from the object storage unit 103.

  Then, the variance value calculation unit 404 specifies an object other than the object identified by the object identifier received from the friend degree calculation unit 409 from the read object. Then, the variance value calculation unit 404 calculates the variance value of the first position based on the position identified by the position information associated with the identified object. Further, the variance value calculation unit 404 calculates the variance value of the first time based on the time identified by the time information associated with the identified object. Further, the variance value calculation unit 404 calculates the variance value of the second position based on the position identified by the position information associated with the read object. Further, the variance value calculation unit 404 calculates the variance value at the second time based on the time identified by the time information associated with the read object.

  The variance value calculation unit 404 is used to calculate the variance value at the first position, the variance value at the first time, the variance value at the second position, the variance value at the second time, and those values. And a set of two or more specific user identifiers are passed to the friendship degree calculation unit 409.

  Next, the configuration of the user terminal 411 will be described.

  The user terminal 411 has the same characteristics as the user terminal 211. Furthermore, the user terminal 411 will output those information, if a user identifier and a friend degree are received from the friend degree calculation part 409. FIG. FIG. 29 is a diagram illustrating an example of the degree of friendship that the user terminal 411 outputs. Referring to FIG. 29, the friendship level increases with time. This represents that the relationship between the persons identified by the user identifier received by the user terminal 411 together with the degree of friendship has become a friendship relationship.

  FIG. 30 is a diagram illustrating an example of an outline of an operation different from the second embodiment of the relationship determination system 40 in the fourth embodiment.

  The object related person acquisition unit 202 stores the user identifier acquired by a predetermined method, the corresponding object, and the position information and time information associated with the object in the object storage unit 103 in association with each other ( Step S401).

  The friend degree calculation unit 409 receives the object identifier of the object stored in the object storage unit 103 by the object related person acquisition unit 202 and the user identifier associated with the object from the object related person acquisition unit 202 (step S402). Then, the friendship degree calculation unit 409 passes the received user identifier and object identifier to the distributed value calculation unit 404.

  The variance value calculation unit 404 receives a user identifier and an object identifier from the friend degree calculation unit 409. The distributed value calculation unit 404 reads the object, position information, and time information associated with all of the two or more specific user identifiers included in the received user identifier from the object storage unit 103 (step S403).

  The variance value calculation unit 404 specifies an object other than the object identified by the object identifier received from the friendship degree calculation unit 409 among the read objects. Then, the variance value calculation unit 404 calculates the variance value of the first position based on the position identified by the position information associated with the identified object. Further, the variance value calculation unit 404 calculates the variance value of the first time based on the time identified by the time information associated with the identified object (step S404). Furthermore, the variance value calculation unit 404 calculates the variance value of the second position based on the position identified by the position information associated with the read object. Further, the variance value calculation unit 404 calculates the variance value at the second time based on the time identified by the time information associated with the read object (step S405).

  The variance value calculation unit 404 calculates the variance value at the first position, the variance value at the first time, the variance value at the second position, the variance value at the second time, and the values used for calculating those values. The set of identifiers is passed to the friendship degree calculation unit 409.

  The friendship degree calculation unit 409 receives from the variance value calculation unit 404 a set of the variance value at the first position, the variance value at the first time, and the user identifier. Also, the friendship degree calculation unit 409 receives from the variance value calculation unit 404 a set of the variance value at the second position, the variance value at the second time, and the user identifier.

  The friendship degree calculation unit 409 calculates the difference between the variance value at the first position and the variance value at the second position, and the difference between the variance value at the first time and the variance value at the second time ( Step S406). Then, the friendship degree calculation unit 409 calculates a friendship degree that indicates a change in the relationship between the persons identified by the user identifier received together with each variance value that is the basis of the difference based on the calculated difference (step) S407).

  The friendship degree calculation unit 409 transmits the user identifier and the friendship degree between persons identified by the user identifier to the user terminal 411.

  When the user terminal 411 receives the user identifier and the friendship degree from the friendship degree calculation unit 409, the user terminal 411 outputs the information (step S408).

  The relationship determination apparatus 400 performs steps S403 to Sunt until all of the user identifiers received by the variance value calculation unit 404 from the friendship degree calculation unit 409 in step S402 are selected as “specific user identifiers” in step S403. The process of S407 may be repeated. For example, the relationship determination apparatus 400 has not selected in step S403 from any two pairs included in the user identifier passed from the friend degree calculation unit 409 to the variance value calculation unit 404 by the process in step S402. You may repeat the process of step S403 thru | or step S407 until there are no pairs. In other words, the relationship determination apparatus 400 selects one arbitrary pair from the user identifiers passed from the friend degree calculation unit 409 to the variance value calculation unit 404 in the process of step S402, and uses the selected pair as an input. Steps S403 to S407 are executed. If there is a pair that has not yet been selected from the two sets included in the user identifier passed from the friend degree calculation unit 409 to the variance value calculation unit 404 by the process of step S402, the relationship determination device 400 Select a pair. The relationship determination apparatus 400 executes the processing from step S403 to step S407 based on the selected set.

  Further, the relationship determination apparatus 400 may receive a user identifier indicating a relationship source and a user identifier indicating a relationship destination by the process of step S402. In this case, the relationship determination apparatus 400 may repeatedly execute the processing from step S403 to step S407 for all combinations of the relationship source user identifier and the relationship destination user identifier. The information indicating the relation source and the information indicating the relation destination may be transmitted from the user terminal 411 to the relationship determination apparatus 400 together with the object. Alternatively, these pieces of information may be stored in advance by the object related person acquisition unit 202.

  The relationship determination system 40 according to the fourth embodiment executes the following process when an object associated with a certain user identifier is stored. That is, the relationship determination system 40 calculates the difference between the position variance values and the time variance value based on the object associated with the specific user identifier included in the user identifier. And the relationship determination system 40 calculates the friendship degree which shows the change of the relationship between the persons identified with the above-mentioned specific user identifier based on each variance value. And the relationship determination system 40 outputs the calculated friendship degree.

  Therefore, the relationship determination system 40 in the fourth embodiment can visualize information that cannot be quantified originally, such as a change in the relationship between specific persons. In addition, the relationship determination system 40 according to the fourth embodiment can output information indicating the relationship between specific persons and the change in the relationship, so the relationship between persons can be determined with higher accuracy. be able to. Further, the user of the relationship determination system 40 can receive information indicating a relationship between specific persons and a change in the relationship, and can determine a relationship between persons with higher accuracy.

[First Modification of Fourth Embodiment]
A part of the configuration of the relationship determination system 30 according to the third embodiment may be added to the relationship determination system 40 according to the fourth embodiment. FIG. 31 is a block diagram illustrating an example of the configuration of the relationship determination system 40 in the first modification example of the fourth embodiment. The relationship determination system 40 in the first modification of the fourth embodiment includes a relationship determination unit 305.

=== Friendship calculator 409 ===
The friendship degree calculation unit 409 executes the following processing when the object related person acquisition unit 202 newly stores an object in the object storage unit 103. That is, the friendship degree calculation unit 409 receives from the object related person acquisition unit 202 a user identifier associated with the object and an object identifier that can identify the object. Then, the friendship degree calculation unit 409 passes the received user identifier and object identifier to the distributed value calculation unit 404.

  The friendship degree calculation unit 409 calculates the variance value at the first position, the variance value at the first time, and the first raw value calculated from the variance value calculation unit 404 based on the objects excluding the new object. An average value of activity line divergence and a set of user identifiers used in calculating those values are received. Also, the friendship degree calculation unit 409 calculates the variance value at the second position, the variance value at the second time, and the second variance value calculated from the variance value calculation unit 404 based on the object to which the new object is added. The average value of the divergence level of the live activity line and a set of user identifiers used in calculating those values are received.

  The friendship degree calculation unit 409 includes a difference between the variance value at the first position and the variance value at the second position, a difference between the variance value at the first time and the variance value at the second time, and the first The difference between the live activity line divergence degree and the second live activity line divergence degree is calculated. Then, the friendship degree calculation unit 409 calculates a friendship degree that indicates a change in the relationship between persons that can be identified by the user identifier received together with each variance value that is the basis of the difference based on the calculated difference.

  For example, the friendship degree calculation unit 409 may specify the linear sum of each difference as the friendship degree as in the following [Equation 8].

  In [Formula 8], F indicates the degree of friendship. Δt indicates a difference in time dispersion values. Δp represents the difference in the variance values of the positions. Δl indicates the difference in the average value of the divergence level of the live activity line. α, β, and γ represent arbitrary real numbers. α, β, and γ may be predetermined values.

  The friendship degree calculation unit 409 transmits to the user terminal 411 a set of user identifiers and a friendship degree between persons who can be identified by those user identifiers.

=== Dispersion Value Calculation Unit 404 ===
The variance value calculation unit 404 receives a user identifier and an object identifier from the friend degree calculation unit 409. Then, the variance value calculation unit 404 obtains an object associated with two or more specific user identifiers among the received user identifiers, a specific user identifier associated with the objects, position information, and time information. Read from the object storage unit 103.

  Then, the variance value calculation unit 404 specifies an object other than the object identified by the object identifier received from the friend degree calculation unit 409 from among the read objects. Then, the variance value calculation unit 404 passes the set of the position information and the user identifier associated with the identified object to the live activity line divergence degree calculation unit 308. Then, the variance value calculation unit 404 receives the first live activity line divergence degree from the live activity line divergence degree calculation unit 308. The variance value calculation unit 404 calculates the average value of the first live activity line divergence based on the received first live activity line divergence.

  The variance value calculation unit 404 passes the position information associated with the object identified by the received object identifier and the user identifier to the live activity line divergence calculation unit 308. Then, the variance value calculation unit 404 receives the second live activity line divergence degree from the live activity line divergence degree calculation unit 308. The variance value calculation unit 404 calculates the average value of the second live activity line divergence based on the first live activity line divergence and the second live activity line divergence.

  The variance value calculation unit 404 is the average value of the variance value at the first position, the variance value at the first time, the variance value at the second position, the variance value at the second time, and the first live activity line divergence degree. And the average value of the second live activity line divergence degree are passed to the friendship degree calculation unit 409. Also, the variance value calculation unit 404 passes the set of user identifiers used when calculating those values to the friendship degree calculation unit 409.

  The relationship determination system 40 in the first modification of the fourth embodiment performs the following process when an object associated with a user identifier that can identify a specific person is stored. That is, the relationship determination system 40 calculates the difference between the position variance values and the time variance value based on the object associated with the specific user identifier included in the user identifier. Furthermore, the relationship determination system 40 calculates the raw activity line divergence based on the object identified based on the specific user identifier and the raw activity line information of the person identified by the specific user identifier, Calculate their average value. And the relationship determination system 40 calculates the friendship degree which shows the change of the relationship between the persons identified with the above-mentioned specific user identifier based on each variance value and the average value of the divergence level of the lifeline. And the relationship determination system 40 outputs the calculated friendship degree.

  Therefore, the relationship determination system 40 in the first modification of the fourth embodiment can visualize information that cannot be quantified originally, such as a change in the relationship between specific persons. In addition, since the criterion for the change in the relationship between the persons is determined by the difference in the degree of divergence of the live activity line based on the live activity line information of each person, Can be customized.

  In addition, the relationship determination system 40 in the first modification of the fourth embodiment can output information indicating the relationship between specific persons and the change in the relationship, so that the person can be more accurately represented. The relationship between them can be determined.

  Further, the user of the relationship determination system 40 can receive information indicating a relationship between specific persons and a change in the relationship, and can determine a relationship between persons with higher accuracy.

  Although the present invention has been described with reference to each embodiment and example, the present invention is not limited to the above embodiment. Various changes that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention.

  In addition, each component in each embodiment of the present invention can be realized by a computer and a program as well as its function in hardware. The program is provided by being recorded on a computer-readable recording medium such as a magnetic disk or a semiconductor memory, and is read by the computer when the computer is started up. The read program causes the computer to function as a component in each of the embodiments described above by controlling the operation of the computer.

  A part or all of the above embodiments can be described as in the following supplementary notes, but is not limited thereto.

(Appendix 1)
An object associated with at least two specific user identifiers among user identifiers that can identify a person, and position information and time information associated with the object are received, and the position of the object is determined based on the received position information and time information. A variance value calculation unit for calculating a variance value and a variance value of time;
If the variance value of the position is equal to or greater than a first threshold value and the variance value of the time is equal to or greater than a second threshold value, it is determined that there is a predetermined relationship between persons identified by the specific user identifier A relationship determination unit;
A relationship determination apparatus comprising:

(Appendix 2)
The relationship determination device according to attachment 1, wherein
The relationship determination unit is configured to identify the position when a variance value at the position is less than the first threshold value and a variance value at the time is less than the second threshold value. A relationship determination apparatus that determines that there is a relationship different from the predetermined relationship between persons identified by the user identifier.

(Appendix 3)
The relationship determination device according to appendix 1 or 2,
The object received by the variance value calculation unit is received from the variance value calculation unit, and a set is identified and identified for each object whose difference between position information and time information associated with the object is equal to or less than a predetermined threshold. An object selection unit that identifies one object for each set and passes the identified object to the variance value calculation unit;
The relationship value calculation unit is a relationship determination device that calculates a position variance value and a time variance value based on an object received from the object selection unit.

(Appendix 4)
The relationship determination device according to any one of appendices 1 to 3,
The relationship determination unit is configured such that the variance value at the position is equal to or greater than the first threshold value, the variance value at the time is equal to or greater than the second threshold value, and the variance value calculation unit includes the variance value of the position and A relationship determination in which it is determined that there is a predetermined relationship between persons identified by the specific user identifier when the number of objects used in calculating the variance value of the time is equal to or greater than a predetermined threshold. apparatus.

(Appendix 5)
The relationship determination device according to any one of appendices 1 to 4,
The variance value calculation unit stores predetermined position information in association with each user identifier,
The variance value calculation unit indicates the position indicated by the position information associated with the received object by the position information stored by itself associated with the user identifier associated with the object. Is converted by associating a predetermined coefficient with the position information,
The variance value calculating unit calculates a variance value of a position based on the converted position information.

(Appendix 6)
The relationship determination device according to any one of appendices 1 to 5,
The variance value calculation unit stores predetermined time information in association with each user identifier,
The variance value calculation unit indicates the time indicated by the time information associated with the received object by the time information stored by itself associated with the user identifier associated with the object. Is converted by associating a predetermined coefficient with the time information,
The variance value calculating unit calculates a variance value of time based on the converted time information.

(Appendix 7)
The relationship determination device according to any one of appendices 1 to 6,
A live activity line storage unit that stores live activity line information indicating a route connecting two or more positions and a user identifier in association with each other;
For each received object, the variance value calculation unit is identified by an arbitrary position on the route identified by the raw activity line information associated with the user identifier included in the object and the position information associated with the object. A live activity line divergence calculation unit that calculates the shortest distance to the position to be calculated and calculates the live activity line divergence corresponding to the calculated shortest distance;
The variance value calculation unit calculates an average value of the live activity line divergence calculated by the live activity line divergence calculation unit,
The relationship determination unit determines that there is a predetermined relationship between the persons identified by the at least two specific user identifiers when the average value calculated by the variance value calculation unit is equal to or greater than a predetermined threshold. A relationship determination device.

(Appendix 8)
The relationship determination device according to attachment 7, wherein
The variance value calculation unit is based on the live activity line divergence degree calculated by the live activity line divergence degree calculation unit and time information associated with the object used when calculating the live activity line divergence degree. Calculating a new degree of divergence, calculating an average value of the calculated new degree of divergence,
The relationship determination unit may determine a predetermined value between the persons identified by the at least two specific user identifiers when an average value of the new divergence calculated by the variance value calculation unit is equal to or greater than a predetermined threshold. A relationship determination device that determines that there is a relationship.

(Appendix 9)
The relationship determination device according to any one of appendices 1 to 8,
An object storage unit that stores an object associated with a user identifier, position information, and time information in association with each other;
A position for receiving an object, acquiring a user identifier that can identify a person identified by the feature information based on the feature information included in the object, and receiving the object, the user identifier, and the object receiving unit together with the object An object-related person acquisition unit that stores information and time information in association with each other in the object storage unit;
When the object-related person acquisition unit stores an object in the object storage unit, the user-related person identifier associated with the object and an object identifier that can identify the object are received, and the received user identifier and the object identifier are received. A friendship degree calculation unit to be passed to the variance value calculation unit,
The variance value calculation unit reads the object, location information, and time information stored in the object storage unit, calculates a variance value of the location and a variance value of the time based on the read location information and time information,
When the variance value calculation unit receives the user identifier and the object identifier from the friend degree calculation unit, the distributed value calculation unit reads out the objects associated with all the received user identifiers from the object storage unit, Calculating a variance value at a first position and a variance value at a first time based on an object other than the object identified by the object identifier;
The variance value calculation unit calculates a variance value at a second position and a variance value at a second time based on the read object,
The variance value calculation unit sends the variance value at the first position, the variance value at the first time, the variance value at the second position, and the variance value at the second time to the friendship degree calculation unit. Hand over,
The friendship degree calculation unit includes a difference between the variance value of the first position and the variance value of the second position, and the variance value of the first time and the variance value of the second time. A relationship determination device that calculates a difference and calculates a friendship degree indicating a change in a relationship between persons identified by a user identifier received from the object related person acquisition unit based on the calculated difference.

(Appendix 10)
The relationship determination apparatus according to attachment 9, wherein
A live activity line storage unit that stores live activity line information indicating a route connecting two or more positions and a user identifier in association with each other;
For each object read by the variance value calculation unit, identification is made by an arbitrary position on the route identified by the raw activity line information associated with the user identifier included in the object and the position information associated with the object. A live activity line divergence calculation unit that calculates the shortest distance to the position to be calculated and calculates the live activity line divergence corresponding to the calculated shortest distance,
The variance value calculation unit calculates, for each object read from the object storage unit based on the user identifier received from the friendship degree calculation unit, a user identifier associated with the object and position information, and the raw activity line To the divergence calculator
The variance calculation unit is a live activity calculated based on an object identified by the object identifier received from the friendship degree calculation unit among the live activity line divergences received from the live activity line divergence calculation unit. The average value of the first activity line divergence is calculated from the activity line divergence other than the line divergence, and the second activity line divergence is calculated from the activity divergence received from the activity line divergence calculation unit. Calculate the average degree,
The variance value calculation unit passes the average value of the first live activity line deviation degree and the average value of the second life activity line deviation degree to the friend degree calculation unit,
The friendship degree calculation unit calculates a difference between an average value of the first live activity line divergence degree and an average value of the second live activity line divergence degree, and the variance value of the first position and the first The difference between the variance value at the second position, the difference between the variance value at the first time and the variance value at the second time, and the average value of the first live activity line divergence and the second live activity A relationship determination device that calculates a friendship degree indicating a change in a relationship between persons identified by a user identifier received from the object related person acquisition unit based on a difference from an average value of the degree of line divergence.

(Appendix 11)
The relationship determination device according to any one of appendices 8 to 10,
The relationship determination unit receives a set of user identifier sets,
For each set of user identifiers received by the relationship determination unit, the variance value calculation unit reads an object associated with all of the user identifiers included in the set from the object storage unit, and the position based on the read object And a variance value of the time are calculated,
The relationship determination unit identifies, based on the position variance value and the time variance value calculated for each set of user identifiers, the user identifier included in the set for all of the user identifier sets. A relationship determination device that changes the predetermined threshold so that the relationship between the persons to be determined is the same.

(Appendix 12)
A user terminal that transmits an object including feature information that is information for identifying a person, position information indicating a position, and time information indicating a time;
An object storage unit for storing an object associated with a user identifier capable of identifying a person, position information indicating a certain position, and time information indicating a certain time in association with each other;
A relationship determination device,
The relationship determination device includes:
An object receiving unit that receives an object, position information, and time information from the user terminal;
Based on the feature information included in the object received by the object receiving unit, a user identifier that can identify the person identified by the feature information is acquired, and the object, the user identifier, and the object receiving unit receive the object together with the object. An object-related person acquisition unit that associates and stores position information and time information in the object storage unit;
When receiving a user identifier from the user terminal, from the object storage unit, an object associated with at least two user identifiers of the received user identifier, position information and time information associated with the object, A variance value calculation unit that calculates a variance value of a position and a variance value of a time based on the read location information and time information;
When the variance value of the position is equal to or greater than a first threshold value and the variance value of the time is equal to or greater than a second threshold value, it is determined that there is a predetermined relationship between the persons identified by the at least two user identifiers. A relationship determination unit that generates information indicating the predetermined relationship in association with the at least two user identifiers;
With
The relationship determination system, wherein the user terminal outputs information indicating the predetermined relationship generated by the relationship determination unit and the at least two user identifiers.

(Appendix 13)
An object associated with at least two specific user identifiers among user identifiers that can identify a person, and position information and time information associated with the object are received, and the position of the object is determined based on the received position information and time information. Calculate the variance and time variance,
If the variance value of the position is equal to or greater than a first threshold value and the variance value of the time is equal to or greater than a second threshold value, it is determined that there is a predetermined relationship between persons identified by the specific user identifier , Relationship determination method.

(Appendix 14)
On the computer,
An object associated with at least two specific user identifiers among user identifiers that can identify a person, and position information and time information associated with the object are received, and the position of the object is determined based on the received position information and time information. Processing to calculate the variance and time variance;
If the variance value of the position is equal to or greater than a first threshold value and the variance value of the time is equal to or greater than a second threshold value, it is determined that there is a predetermined relationship between persons identified by the specific user identifier And a relationship determination program for executing the process.

  The relationship determination system in each aspect of the present invention can be used as a system that provides a service according to the relationship between persons.

DESCRIPTION OF SYMBOLS 20 Relationship determination system 30 Relationship determination system 40 Relationship determination system 100 Relationship determination apparatus 200 Relationship determination apparatus 300 Relationship determination apparatus 400 Relationship determination apparatus 201 Object receiving part 202 Object related person acquisition part 103 Object storage part 104 Variance value calculation unit 304 Variance value calculation unit 404 Variance value calculation unit 105 Relationship determination unit 205 Relationship determination unit 305 Relationship determination unit 106 Object selection unit 307 Live activity line storage unit 308 Live activity line divergence calculation unit 409 Friends Degree calculation unit 211 User terminal 411 User terminal 1000 User input 1001 Address book

Claims (14)

An object associated with at least two specific user identifiers among user identifiers that can identify a person, and position information and time information associated with the object are received, and the position of the object is determined based on the received position information and time information. A variance value calculation unit for calculating a variance value and a variance value of time;
If the variance value of the position is equal to or greater than a first threshold value and the variance value of the time is equal to or greater than a second threshold value, it is determined that there is a predetermined relationship between persons identified by the specific user identifier A relationship determination unit;
A relationship determination apparatus comprising: It is the relationship determination apparatus of Claim 1, Comprising:
The relationship determination unit is configured to identify the position when a variance value at the position is less than the first threshold value and a variance value at the time is less than the second threshold value. A relationship determination apparatus that determines that there is a relationship different from the predetermined relationship between persons identified by the user identifier. The relationship determination device according to claim 1 or 2,
The object received by the variance value calculation unit is received from the variance value calculation unit, and a set is identified and identified for each object whose difference between position information and time information associated with the object is equal to or less than a predetermined threshold. An object selection unit that identifies one object for each set and passes the identified object to the variance value calculation unit;
The relationship value calculation unit is a relationship determination device that calculates a position variance value and a time variance value based on an object received from the object selection unit. It is the relationship determination apparatus of any one of Claims 1 thru | or 3, Comprising:
The relationship determination unit is configured such that the variance value at the position is equal to or greater than the first threshold value, the variance value at the time is equal to or greater than the second threshold value, and the variance value calculation unit includes the variance value of the position and A relationship determination in which it is determined that there is a predetermined relationship between persons identified by the specific user identifier when the number of objects used in calculating the variance value of the time is equal to or greater than a predetermined threshold. apparatus. The relationship determination device according to any one of claims 1 to 4, wherein
The variance value calculation unit stores predetermined position information in association with each user identifier,
The variance value calculation unit indicates the position indicated by the position information associated with the received object by the position information stored by itself associated with the user identifier associated with the object. Is converted by associating a predetermined coefficient with the position information,
The variance value calculating unit calculates a variance value of a position based on the converted position information. The relationship determination device according to any one of claims 1 to 5,
The variance value calculation unit stores predetermined time information in association with each user identifier,
The variance value calculation unit indicates the time indicated by the time information associated with the received object by the time information stored by itself associated with the user identifier associated with the object. Is converted by associating a predetermined coefficient with the time information,
The variance value calculating unit calculates a variance value of time based on the converted time information. It is the relationship determination apparatus of any one of Claims 1 thru | or 6, Comprising:
A live activity line storage unit that stores live activity line information indicating a route connecting two or more positions and a user identifier in association with each other;
For each received object, the variance value calculation unit is identified by an arbitrary position on the route identified by the raw activity line information associated with the user identifier included in the object and the position information associated with the object. A live activity line divergence calculation unit that calculates the shortest distance to the position to be calculated and calculates the live activity line divergence corresponding to the calculated shortest distance,
The variance value calculation unit calculates an average value of the live activity line divergence calculated by the live activity line divergence calculation unit,
The relationship determination unit determines that there is a predetermined relationship between the persons identified by the at least two specific user identifiers when the average value calculated by the variance value calculation unit is equal to or greater than a predetermined threshold. A relationship determination device. It is the relationship determination apparatus of Claim 7, Comprising:
The variance value calculation unit is based on the live activity line divergence degree calculated by the live activity line divergence degree calculation unit and time information associated with the object used when calculating the live activity line divergence degree. Calculating a new degree of divergence, calculating an average value of the calculated new degree of divergence,
The relationship determination unit may determine a predetermined value between the persons identified by the at least two specific user identifiers when an average value of the new divergence calculated by the variance value calculation unit is equal to or greater than a predetermined threshold. A relationship determination device that determines that there is a relationship. The relationship determination device according to any one of claims 1 to 8,
An object storage unit that stores an object associated with a user identifier, position information, and time information in association with each other;
A position for receiving an object, acquiring a user identifier that can identify a person identified by the feature information based on the feature information included in the object, and receiving the object, the user identifier, and the object receiving unit together with the object An object-related person acquisition unit that stores information and time information in association with each other in the object storage unit;
When the object-related person acquisition unit stores an object in the object storage unit, the user-related person identifier associated with the object and an object identifier that can identify the object are received, and the received user identifier and the object identifier are received. A friendship degree calculation unit to be passed to the variance value calculation unit,
The variance value calculation unit reads the object, location information, and time information stored in the object storage unit, calculates a variance value of the location and a variance value of the time based on the read location information and time information,
When the variance value calculation unit receives the user identifier and the object identifier from the friend degree calculation unit, the distributed value calculation unit reads out the objects associated with all the received user identifiers from the object storage unit, Calculating a variance value at a first position and a variance value at a first time based on an object other than the object identified by the object identifier;
The variance value calculation unit calculates a variance value at a second position and a variance value at a second time based on the read object,
The variance value calculation unit sends the variance value at the first position, the variance value at the first time, the variance value at the second position, and the variance value at the second time to the friendship degree calculation unit. Hand over,
The friendship degree calculation unit includes a difference between the variance value of the first position and the variance value of the second position, and the variance value of the first time and the variance value of the second time. A relationship determination device that calculates a difference and calculates a friendship degree indicating a change in a relationship between persons identified by a user identifier received from the object related person acquisition unit based on the calculated difference. It is the relationship determination apparatus of Claim 9, Comprising:
A live activity line storage unit that stores live activity line information indicating a route connecting two or more positions and a user identifier in association with each other;
For each object read by the variance value calculation unit, identification is made by an arbitrary position on the route identified by the raw activity line information associated with the user identifier included in the object and the position information associated with the object. A live activity line divergence calculation unit that calculates the shortest distance to the position to be calculated and calculates the live activity line divergence corresponding to the calculated shortest distance,
The variance value calculation unit calculates, for each object read from the object storage unit based on the user identifier received from the friendship degree calculation unit, a user identifier associated with the object and position information, and the raw activity line To the divergence calculator
The variance calculation unit is a live activity calculated based on an object identified by the object identifier received from the friendship degree calculation unit among the live activity line divergences received from the live activity line divergence calculation unit. The average value of the first activity line divergence is calculated from the activity line divergence other than the line divergence, and the second activity line divergence is calculated from the activity divergence received from the activity line divergence calculation unit. Calculate the average degree,
The variance value calculation unit passes the average value of the first live activity line deviation degree and the average value of the second life activity line deviation degree to the friend degree calculation unit,
The friendship degree calculation unit calculates a difference between an average value of the first live activity line divergence degree and an average value of the second live activity line divergence degree, and the variance value of the first position and the first The difference between the variance value at the second position, the difference between the variance value at the first time and the variance value at the second time, and the average value of the first live activity line divergence and the second live activity A relationship determination device that calculates a friendship degree indicating a change in a relationship between persons identified by a user identifier received from the object related person acquisition unit based on a difference from an average value of the degree of line divergence. It is the relationship determination apparatus of any one of Claims 8 thru | or 10, Comprising:
The relationship determination unit receives a set of user identifier sets,
For each set of user identifiers received by the relationship determination unit, the variance value calculation unit reads an object associated with all of the user identifiers included in the set from the object storage unit, and the position based on the read object And a variance value of the time are calculated,
The relationship determination unit identifies, based on the position variance value and the time variance value calculated for each set of user identifiers, the user identifier included in the set for all of the user identifier sets. A relationship determination device that changes the predetermined threshold so that the relationship between the persons to be determined is the same. A user terminal that transmits an object including feature information that is information for identifying a person, position information indicating a position, and time information indicating a time;
An object storage unit for storing an object associated with a user identifier capable of identifying a person, position information indicating a certain position, and time information indicating a certain time in association with each other;
A relationship determination device,
The relationship determination device includes:
An object receiving unit that receives an object, position information, and time information from the user terminal;
Based on the feature information included in the object received by the object receiving unit, a user identifier that can identify the person identified by the feature information is acquired, and the object, the user identifier, and the object receiving unit receive the object together with the object. An object-related person acquisition unit that associates and stores position information and time information in the object storage unit;
When receiving a user identifier from the user terminal, from the object storage unit, an object associated with at least two user identifiers of the received user identifier, position information and time information associated with the object, A variance value calculation unit that calculates a variance value of a position and a variance value of a time based on the read location information and time information;
When the variance value of the position is equal to or greater than a first threshold value and the variance value of the time is equal to or greater than a second threshold value, it is determined that there is a predetermined relationship between the persons identified by the at least two user identifiers. A relationship determination unit that generates information indicating the predetermined relationship in association with the at least two user identifiers;
With
The relationship determination system, wherein the user terminal outputs information indicating the predetermined relationship generated by the relationship determination unit and the at least two user identifiers. An object associated with at least two specific user identifiers among user identifiers that can identify a person, and position information and time information associated with the object are received, and the position of the object is determined based on the received position information and time information. Calculate the variance and time variance,
If the variance value of the position is equal to or greater than a first threshold value and the variance value of the time is equal to or greater than a second threshold value, it is determined that there is a predetermined relationship between persons identified by the specific user identifier , Relationship determination method. On the computer,
An object associated with at least two specific user identifiers among user identifiers that can identify a person, and position information and time information associated with the object are received, and the position of the object is determined based on the received position information and time information. Processing to calculate the variance and time variance;
If the variance value of the position is equal to or greater than a first threshold value and the variance value of the time is equal to or greater than a second threshold value, it is determined that there is a predetermined relationship between persons identified by the specific user identifier And a relationship determination program for executing the process.

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