Identifying unexpected relationships in a social networking system

US10319045B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-10319045-B2
Application numberUS-201213685584-A
CountryUS
Kind codeB2
Filing dateNov 26, 2012
Priority dateNov 26, 2012
Publication dateJun 11, 2019
Grant dateJun 11, 2019

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  5. First independent claim

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Abstract

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A social networking system identifies relationships between friends of a target user that are likely to be unexpected to the target user. To identify an unexpected relationship among a user's friends, the social networking system determines a measure of unexpectedness for pairs of connections of the target user and selects pairs of connections for presentation to the user based on the measure of unexpectedness. The measure of unexpectedness of a relationship between a pair of friends is inversely related to a number of connections between each of the pair of friends and the target user. Information describing the pair of unexpected friends may be presented to a target user along with content relating the two friends, such as photos in which both friends are tagged, events attended by the unexpected friends together, or places both unexpected friends checked-in at the same time.

First claim

Opening claim text (preview).

What is claimed is: 1. A computer implemented method comprising: storing, by a social networking system, data representing a social graph comprising objects of the social networking system and connections describing relationships among the objects, the objects comprising a plurality of user profile objects representing users of the social networking system and a plurality of content objects; identifying a target object, the target object connected to some of the plurality of user profile objects in the social graph; identifying one or more pairs of user profile objects that are connected to the target object, the data representing the social graph indicating that the user profile objects in each pair are connected to each other in the social graph; determining, for each of the identified pairs, a measure of unexpectedness with respect to the target object, the measure of unexpectedness indicative of a likelihood that the identified pair being connected is unexpected to a target user of the social networking system who is represented by the target object in the social graph, the determining comprising: for each identified pair having a first identified object and a second identified object: (i) identifying a first subset of the plurality of user profile objects that are connected to both the first identified object and the target object; (ii) identifying a second subset of the plurality of user profile objects that are connected to both the second identified object and the target object; (iii) identifying a third subset of the plurality of user profile objects that are connected to the first identified object, the second identified object, the target object; (iv) determining the measure of unexpectedness as a value that is positively related to both a first number of objects in the first subset and a second number of objects in the second subset and that is inversely related to a third number of objects in the third subset; determining, for each of the identified pairs, whether the identified pair belongs to a false positive based on determining whether a content object in the social graph is connected to the first identified object, the second identified object and the target object; removing one or more of the identified pairs that are determined as false positives from selection; selecting one of the identified pairs based on the measure of unexpectedness with respect to the target object; selecting a particular content item associated with the selected pair; and transmitting the particular content item to the target user who is represented by the target object in the social graph. 2. The computer implemented method of claim 1 , wherein the one or more of the identified pairs that are classified as false positives are classified further based on determining, for an identified pair, that the first identified object or the second identified object represents a spouse of the target user in the social graph. 3. The computer implemented method of claim 1 , wherein determining whether a content object in the social graph is connected to the first identified object, the second identified object and the target object comprises determining whether the first identified object, the second object and the target object are each tagged in the content item in the social networking system. 4. The computer implemented method of claim 1 , further comprising, for each identified pair: determining that the first identified object or the second identified object represents a spouse of the target user; and decreasing the measure of unexpectedness. 5. The computer implemented method of claim 1 , wherein the plurality of content objects each represents a content item selected from a group consisting of: an image, a check-in, a post, and any combination thereof. 6. The computer implemented method of claim 1 , further comprising, for each of the identified pairs: determining that the first identified object, the second identified object and the target object represent members of the same group in the social networking system; and decreasing the measure of unexpectedness. 7. The computer implemented method of claim 1 , further comprising: increasing the measure of unexpectedness for a particular identified pair based on an affinity between the first identified object and the second identified object. 8. The computer implemented method of claim 1 , wherein the transmitted particular content item is transmitted with a description of unexpectedness of the selected pair to the target user. 9. The method of claim 1 further comprising: clustering the plurality of user profile objects in the social graph connected to the target object into a plurality of clusters, wherein, for at least one of the identified pairs, the first identified object is clustered in a first cluster and the second identified object is clustered in a second cluster. 10. A non-transitory computer-readable storage medium storing computer-executable instructions, the instructions, when executed by a processor, cause the processor to perform steps comprising: storing, by a social networking system, data representing a social graph comprising objects of the social networking system and connections describing relationships among the objects, the objects comprising a plurality of user profile objects representing users of the social networking system and a plurality of content objects, identifying a target object, the target object connected to some of the plurality of user profile objects in the social graph; identifying one or more pairs of user profile objects that are connected to the target object, the data representing the social graph indicating that the user profile objects in each pair are connected to each other in the social graph; determining, for each of the identified pairs, a measure of unexpectedness with respect to the target object, the measure of unexpectedness indicative of a likelihood that the identified pair being connected is unexpected to a target user of the social networking system who is represented by the target object in the social graph, the determining comprising: for each identified pair having a first identified object and a second identified object: (i) identifying a first subset of the plurality of user profile objects that are connected to both the first identified object and the target object; (ii) identifying a second subset of the plurality of user profile objects that are connected to both the second identified object and the target object, (iii) identifying a third subset of the plurality of user profile objects that are connected to the first identified object, the second identified object, the target object; (iv) determining the measure of unexpectedness as a value that is positively related to both a first number of objects in the first subset and a second number of objects in the second subset and that is inversely related to a third number of objects in the third subset; determining, for each of the identified pairs, whether the identified pair belongs to a false positive based on determining whether a content object in the social graph is connected to the first identified object, the second identified object and the target object; removing one or more of the identified pairs that are determined as false positives from selection; selecting one of the identified pairs based on the measure of unexpectedness with respect to the target object; selecting a particular content item associated with the selected pair; and transmitting the particular content item to the target user who is represented by the target object in the social graph. 11. The non-transitory computer-readable s

Assignees

Inventors

Classifications

  • G06Q10/40Primary

    Business processes related to social networking or social networking services · CPC title

  • G06Q50/01Primary

    Physics · mapped topic

  • using social graphs · CPC title

  • G06Q10/42Primary

    Determination of affinities or common interests between users · CPC title

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What does patent US10319045B2 cover?
A social networking system identifies relationships between friends of a target user that are likely to be unexpected to the target user. To identify an unexpected relationship among a user's friends, the social networking system determines a measure of unexpectedness for pairs of connections of the target user and selects pairs of connections for presentation to the user based on the measure o…
Who is the assignee on this patent?
Frank Jonathan H, Facebook Inc
What technology area does this patent fall under?
Primary CPC classification G06Q10/40. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Jun 11 2019 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).