SYSTEM AND METHOD FOR LOCATION-BASED RECOMMENDATIONS

• US 20130054698A1
• Filed: 08/22/2012
• Published: 02/28/2013
• Est. Priority Date: 08/22/2011
• Status: Active Grant

• Current Assignee: Johnny Lee
• Original Assignee: Johnny Hsienchow Lee
• Inventors: LEE, JOHNNY Hsienchow, TSE, CHUN TO
• Granted Patent: US 9,208,511 B2
• Time in Patent Office: Days
• US Class Current: 709/204
• CPC Class Codes: G06Q 30/0259 based on store location
• CPC Class Codes: G06Q 30/0261 based on user location
• CPC Class Codes: G06Q 30/0267 Wireless devices
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: H04W 4/023 using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
• CPC Class Codes: H04W 4/21 for social networking applications

Abstract

A method for providing a recommendation to a user, including retrieving, connection content associated with social network connections of the user; calculating, for each of the social network connections, an influence score for each of a plurality of locations; receiving a request location from a user device associated with the user; extracting a recommendation from relevant connection content, the relevant connection content being content associated with the request location and generated by at least one of the social network connections having the highest influence scores for the request location, the recommendation comprising a venue referenced within the relevant connection content; and sending the recommendation to the user device.

Claims

1. A method for determining and utilizing a user influence score, comprising:

retrieving user activities from a social network, the user activities comprising activities, associated with the social network, by the user;

retrieving connection activities from the social network, the connection activities comprising activities, associated with the social network, by primary connections, the primary connections comprising social network connections of the user;

calculating, for the user, a user influence score for each of a plurality of locations based on;

the volume of user actions proximal the location;

an influence score of each primary connection for the location, based on the volume of connection activities of the social network connection proximal the geographic location; and

an engagement level between the primary connection and the user, based on a history of social network interactions between the user and the primary connection; and

sending data derived from the user influence score to a mobile module.

2. The method of claim 1, wherein calculating the influence score comprises increasing the user influence score with decreasing distance between the user activity and the location.

3. The method of claim 1, wherein calculating the influence score comprises increasing the user influence score with decreasing time duration between a time associated with the user activity and a time of calculation.

4. The method of claim 1, wherein calculating the influence score further comprises adjusting the user influence score by a location density for each of the plurality of locations.

5. The method of claim 4, wherein adjusting the user influence score comprises adjusting the user influence score for the location inversely with the location density for the location.

6. The method of claim 1, wherein calculating the user influence score further comprises calculating a topical influence score for a topic based on:

the volume of user actions related to the topic;

the general engagement level with the user for the topic;

an influence score of each primary connection for the topic, based on the volume of connection activities generated by the primary connection and associated with the topic; and

the engagement level between the primary connection and the user.

7. The method of claim 1, wherein calculating the user influence score for each of a plurality of locations is further based on an influence score of secondary connections on the location, the secondary connections comprising the social network connections of the primary connection.

8. The method of claim 1, wherein sending data derived from the user influence score to a mobile module is performed in response to receiving a request location from a second user, the second user being a social network connection of the first user, wherein sending data derived from the user influence score to a mobile module comprises:

determining that the user influence score is higher than influence scores of other social network connections of the second user;

extracting a recommendation from the user actions associated with the request location;

sending the recommendation to a mobile module associated with the second user;

determining a response from the second user; and

adjusting the user influence score based on the response.

9. The method of claim 1, wherein the user influence score is increased when the response is a positive response, and decreased when the response is a negative response.

10. A method for providing a location-based recommendation for a user, the method comprising:

retrieving, from a social network, connection content associated with primary connections, the primary connections comprising social network connections of the user;

calculating, for each of the primary connections, an influence score for each of a plurality of locations based on;

the volume of connection content associated with the primary connection and associated with the location, and

an engagement level between the primary connection and the user, the engagement level based on a history of social network interaction between the primary connection and the user;

receiving a request location from a user device associated with the user;

extracting a recommendation from relevant connection content, the relevant connection content being content associated with the request location and generated by at least one of the primary connections having the highest influence scores for the request location, the recommendation comprising a venue referenced within the relevant connection content; and

sending the recommendation to the user device.

11. The method of claim 10, further comprising retrieving, from the social network, secondary connection content generated by secondary connections, the secondary connections comprising social network connections of the primary connections;

wherein calculating the influence score for each of the primary connections for each of a plurality of locations is further based on;

an influence score of each of the secondary connections of the primary connection for the location, based on the volume of secondary connection content generated by the secondary connection and associated with the location; and

an engagement level between the secondary connection and the primary connection, based on a history of social network interaction between the secondary connection and the primary connection.

12. The method of claim 11, wherein calculating the influence score further comprises calculating a topical influence score for each of a plurality of topics for each of the plurality of primary connections based on:

the volume of connection content generated by the primary connection and associated with the topic;

a topical influence score of each of the secondary connections of the primary connection for the topic, based on a volume of secondary connection content generated by the secondary connection and associated with the topic, and

the engagement level between the secondary connection and the primary connection.

13. The method of claim 10, wherein calculating the influence score further comprises calculating a topical influence score for each of a plurality of topics for each of the plurality of primary connections, the topical influence score calculated based on the volume of connection content generated by the primary connection and associated with the topic.

14. The method of claim 13, further comprising receiving a request topic from the user device;

wherein extracting the recommendation from the relevant connection content further comprises extracting the recommendation from relevant connection content generated by at least one of the primary connections having the highest topical influence scores for the request topic.

15. The method of claim 10, wherein extracting a recommendation from relevant connection content comprises identifying a repeatedly referenced venue associated with the relevant connection content.

16. The method of claim 15, wherein extracting a recommendation from relevant connection content further comprises extracting a recommendation from relevant connection content that is generated within a predetermined period of time.

17. The method of claim 15, wherein extracting a recommendation from relevant connection content further comprises extracting the recommendation from relevant connection content that is generated by multiple primary connections with the highest influence scores.

18. The method of claim 10, further comprising:

storing the influence scores for each primary connection for each location in a user file;

retrieving, from the social network, content generated by the user;

generating a user profile, comprising;

extracting a plurality of keywords, indicative of user preferences, from the content; and

storing the keywords within the user file;

wherein extracting a recommendation from the relevant connection content further comprises filtering the relevant connection content with keywords from the user profile.

19. The method of claim 18, wherein generating a user profile further comprises identifying a distance limit, wherein extracting a recommendation from the relevant connection content further comprises filtering the venues extracted from the relevant connection content with the distance limit.

20. The method of claim 18, further comprising determining a user response to the recommendation;

and adjusting the user file based on the user response.

21. The method of claim 20, wherein determining the user response comprises detecting generation of content referencing the recommendation;

wherein adjusting the user file comprises increasing the influence score of the primary connection from which the recommendation was derived.

22. The method of claim 21, wherein increasing the influence score of the primary connection comprises increasing the influence score of the primary connection for the request location and increasing the influence score of the primary connection for locations associated with the request location.

23. The method of claim 20, wherein adjusting the user file comprises adjusting a weighting of a keyword associated with the recommendation within the user profile.

24. The method of claim 20, wherein determining the user response comprises detecting generation of content referencing a venue different from the recommendation, the content being generated within a predetermined time duration from a time of request location receipt;

wherein adjusting the user file comprises decreasing the influence score of the primary connection from which the recommendation was derived.