SYSTEMS AND METHODS TO FACILITATE SEARCHES BASED ON SOCIAL GRAPHS AND AFFINITY GROUPS

• US 20130282706A1
• Filed: 03/15/2013
• Published: 10/24/2013
• Est. Priority Date: 05/06/2008
• Status: Active Grant

• Current Assignee: Thryv, Inc. (Mudrick Capital Management LP)
• Original Assignee: YellowPages.com LLC (Mudrick Capital Management LP)
• Inventors: Yoo, David
• Granted Patent: US 8,868,552 B2
• Time in Patent Office: Days
• US Class Current: 707/723
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

Business, recommendation, and social relationship graph information for businesses may be received from a data source social networking website, where each business is recommended by users. The recommendation information may indicate users that recommend certain businesses. The social relationship graph information may indicate user-specific networks of social relationships on the social networking website. For a user query including business and affinity group selection criteria, business, recommendation, and social relationship graph information may be searched to select businesses that: match the business selection criteria; and are recommended by users having social relationships within a maximum degree of closeness with the querying user and being in an affinity group matching the affinity group selection criteria. The selected businesses may be ranked based on numbers of recommending users and social relationship graph information. A search result, with businesses indicated in a rank order and with business and recommendation information, may be provided.

Claims

1. (canceled)

2. A system for searching for businesses at least partially based on social graph information and affinity group information, the system comprising:

one or more network interfaces accessible from a network;

one or more repositories to retain one or more of;

business information;

social graph information;

user preference information relating to the business information; and

/or affinity group information;

one or more processors coupled to at least one of the one or more network interfaces and to at least one of the one or more repositories, the one or more processors to execute instructions to;

process an input corresponding to a query that is associated with an identified user, the input being received via a network and comprising business selection criteria;

search the business information to identify a set of businesses based at least in part on the business selection criteria;

process the social graph information relating to a set of users to identify information about one or more networks of social relationships between two or more users of the set of users, the one or more networks of social relationships being associated with one or more social networking websites, wherein the set of users comprises the identified user;

process the user preference information relating to the set of businesses, the user preference information indicating that, for one or more businesses of the set of businesses, one or more users of the set of users have indicated one or more preferences for the one or more businesses of the set of businesses;

process the affinity group information to identify one or more affinity groups corresponding to the input;

rank one or more businesses of the set of businesses based at least in part on;

at least some of the social relationship graph information;

at least some of the user preference information relating to the plurality of businesses; and

at least some of the affinity group information; and

generate a search result based at least in part on the ranking of the one or more businesses.

3. The system of claim 2, wherein the input comprises affinity group selection criteria, and the one or more affinity groups corresponding to the input are identified based at least in part on the affinity group selection criteria.

4. The system of claim 2, wherein affinity group selection criteria is determined based at least in part on the business selection criteria, and the one or more affinity groups corresponding to the input are identified based at least in part on the affinity group selection criteria.

5. The system of claim 2, wherein the ranking the one or more businesses of the set of businesses based at least in part on at least some of the social relationship graph information comprises differentiating between degrees of relation to the identified user, and wherein the search result comprises a representation of at least one of the set of businesses, the representation indicating one or more of the degrees of relation to the identified user.

6. The system of claim 2, wherein the ranking the one or more businesses of the set of businesses based at least in part on at least some of the user preference information relating to the plurality of businesses comprises determining numbers of users of the set of users that have indicated one or more preferences for the one or more businesses of the set of businesses, and wherein the search result comprises a representation of at least one of the set of businesses, the representation indicating one or more of the numbers of users of the set of users that have indicated one or more preferences.

7. The system of claim 2, wherein the ranking the one or more businesses of the set of businesses based at least in part on at least some of the affinity group information comprises determining a relevance of one or more affinity groups to the business selection criteria, and determining numbers of users of the set of users that are associated with the one or more affinity groups.

8. The system of claim 7, wherein the search result comprises a representation of at least one of the set of businesses, the representation indicating one or more of the numbers of users of the set of users that have indicated one or more preferences.

15. The method of claim 7, wherein the search result comprises a representation of at least one of the set of businesses, the representation indicating one or more of the numbers of users of the set of users that have indicated one or more preferences.

9. A method for searching for businesses at least partially based on social graph information and affinity group information, the method comprising:

receiving, by a computing system, an input corresponding to a query that is associated with an identified user, the input being received via a network and comprising business selection criteria;

searching, via the computing system, business information to identify a set of businesses based at least in part on the business selection criteria;

processing, via the computing device, social graph information relating to a set of users to identify information about one or more networks of social relationships between two or more users of the set of users, the one or more networks of social relationships being associated with one or more social networking websites, wherein the set of users comprises the identified user;

processing, via the computing system, user preference information relating to the set of businesses, the user preference information indicating that, for one or more businesses of the set of businesses, one or more users of the set of users have indicated one or more preferences for the one or more businesses of the set of businesses;

processing, via the computing system, affinity group information to identify one or more affinity groups corresponding to the input;

ranking, via the computing system, one or more businesses of the set of businesses based at least in part on;

at least some of the social relationship graph information;

at least some of the user preference information relating to the plurality of businesses; and

at least some of the affinity group information; and

providing, over the network, a search result based at least in part on the ranking of the one or more businesses.

10. The method of claim 9, wherein the input comprises affinity group selection criteria, and the one or more affinity groups corresponding to the input are identified based at least in part on the affinity group selection criteria.

11. The method of claim 9, wherein affinity group selection criteria is determined based at least in part on the business selection criteria, and the one or more affinity groups corresponding to the input are identified based at least in part on the affinity group selection criteria.

12. The method of claim 9, wherein the ranking the one or more businesses of the set of businesses based at least in part on at least some of the social relationship graph information comprises differentiating between degrees of relation to the identified user, and wherein the search result comprises a representation of at least one of the set of businesses, the representation indicating one or more of the degrees of relation to the identified user.

13. The method of claim 9, wherein the ranking the one or more businesses of the set of businesses based at least in part on at least some of the user preference information relating to the plurality of businesses comprises determining numbers of users of the set of users that have indicated one or more preferences for the one or more businesses of the set of businesses, and wherein the search result comprises a representation of at least one of the set of businesses, the representation indicating one or more of the numbers of users of the set of users that have indicated one or more preferences.

14. The method of claim 9, wherein the ranking the one or more businesses of the set of businesses based at least in part on at least some of the affinity group information comprises determining a relevance of one or more affinity groups to the business selection criteria, and determining numbers of users of the set of users that are associated with the one or more affinity groups.

16. A non-transitory machine-readable medium having machine-readable instructions thereon for searching for businesses at least partially based on social graph information and affinity group information, which instructions, when executed by one or more computers or other processing devices, causes the one or more instructions to:

process an input corresponding to a query that is associated with an identified user, the input being received via a network and comprising business selection criteria;

search business information to identify a set of businesses based at least in part on the business selection criteria;

process social graph information relating to a set of users to identify information about one or more networks of social relationships between two or more users of the set of users, the one or more networks of social relationships being associated with one or more social networking websites, wherein the set of users comprises the identified user;

process user preference information relating to the set of businesses, the user preference information indicating that, for one or more businesses of the set of businesses, one or more users of the set of users have indicated one or more preferences for the one or more businesses of the set of businesses;

process affinity group information to identify one or more affinity groups corresponding to the input;

rank one or more businesses of the set of businesses based at least in part on;

at least some of the social relationship graph information;

at least some of the user preference information relating to the plurality of businesses; and

at least some of the affinity group information; and

generate a search result based at least in part on the ranking of the one or more businesses.

17. The non-transitory machine-readable medium of claim 16, wherein the input comprises affinity group selection criteria, and the one or more affinity groups corresponding to the input are identified based at least in part on the affinity group selection criteria.

18. The non-transitory machine-readable medium of claim 16, wherein affinity group selection criteria is determined based at least in part on the business selection criteria, and the one or more affinity groups corresponding to the input are identified based at least in part on the affinity group selection criteria.

19. The non-transitory machine-readable medium of claim 16, wherein the ranking the one or more businesses of the set of businesses based at least in part on at least some of the social relationship graph information comprises differentiating between degrees of relation to the identified user, and wherein the search result comprises a representation of at least one of the set of businesses, the representation indicating one or more of the degrees of relation to the identified user.

20. The non-transitory machine-readable medium of claim 16, wherein the ranking the one or more businesses of the set of businesses based at least in part on at least some of the user preference information relating to the plurality of businesses comprises determining numbers of users of the set of users that have indicated one or more preferences for the one or more businesses of the set of businesses, and wherein the search result comprises a representation of at least one of the set of businesses, the representation indicating one or more of the numbers of users of the set of users that have indicated one or more preferences.

21. The non-transitory machine-readable medium of claim 16, wherein the ranking the one or more businesses of the set of businesses based at least in part on at least some of the affinity group information comprises determining a relevance of one or more affinity groups to the business selection criteria, and determining numbers of users of the set of users that are associated with the one or more affinity groups.