Matching social network users

• US 8,117,272 B1
• Filed: 10/10/2011
• Issued: 02/14/2012
• Est. Priority Date: 11/20/2008
• Status: Active Grant

• Current Assignee: Melissa Leonard
• Original Assignee: MeetMyKind LLC
• Inventors: Leonard, Melissa
• Primary Examiner(s): Nguyen, Quang N.
• Application Number:
  US13/270,011
• Publication Number:
  US 20120030287A1
• Time in Patent Office: 127 Days
• Field of Search: 709/203, 709/204, 709/206, 709/217, 709/219, 709/224, 709/226, 709/228
• US Class Current: 709/206
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

Systems and methods are disclosed for matching of individuals to one another using a matching model. The matching model matches social network users based on ratings given by users one to another, as well as, as appropriate and available, explicit attributes indicated by users and other data such as location data and system usage data.

Claims

1. A process for recommending prospects to social network users, the process comprising:

obtaining personal attribute information from a first plurality of the users;

obtaining desired-prospect attribute information from a second plurality of the users;

recommending prospects to a third plurality of the users, wherein the recommended prospects have acceptable proximities to the third plurality of users based upon ratings, the desired-prospect attribute information and the personal attribute information, wherein the ratings reflect a quality of match;

wherein at least some of the users are also prospects, the process further comprising identifying users that have rated each other high and low, and using these identifications in conjunction with an estimate of how similar one user is to the other to derive ratings as estimates of how the users will rate other users that they have not yet rated;

wherein recommending comprises scoring user-prospect matches to indicate quality of match between respective prospects and users, wherein the scores are derived from weighting plural matched attribute information of the prospects to the users'"'"' desired-prospect attributes.

2. The process of claim 1 further comprising obtaining the ratings from a fourth plurality of the users.

3. The process of claim 1 further comprising obtaining the ratings by estimating which users are most like other users based on users having similar ratings of other users.

4. The process of claim 1 further comprising providing to a fifth plurality of the users respective preliminary lists of prospects, and obtaining from the fifth plurality of users each user'"'"'s rating of the prospects in the user'"'"'s respective preliminary list,

wherein the ratings reflect the user'"'"'s opinion of a quality of match of the prospects in the preliminary list,

wherein the fifth plurality of the users comprises a subset of the first plurality of users, the second plurality of users and the third plurality of the users.

5. The process of claim 1 wherein if a prospect is deemed to be a potential match for a given user based on a combination of proximity data and other data, then evaluating whether the prospect'"'"'s attributes match the user'"'"'s desired-attributes.

6. The process of claim 1 wherein recommending further comprises categorizing the prospects.

7. The process of claim 6 wherein the categories are selected from the group consisting of dating, friendship, activities, networking, deal making and reuniting.

8. The process of claim 1 wherein at least some of the users rate other users.

9. The process of claim 1 wherein recommending further comprises scoring matches of users and prospects.

10. The process of claim 9 further comprising adjusting the scores based on the attributes of the prospect being rated.

11. The process of claim 9 further comprising adjusting the scores based on the ratings.

12. The process of claim 1 further comprising invalidating ratings by a given user if the given user has a pattern of ratings which fail to correlate to ratings by other users.

13. An apparatus comprising a machine readable storage memory storing a program having instructions which when executed by a processor will cause the processor to recommend prospects to social network users, the instructions of the program for:

obtaining personal attribute information from a first plurality of the users;

obtaining desired-prospect attribute information from a second plurality of the users;

recommending prospects to a third plurality of the users, wherein the recommended prospects have acceptable proximities to the third plurality of users based upon ratings, the desired-prospect attribute information and the personal attribute information, wherein the ratings reflect a quality of match;

wherein at least some of the users are also prospects, the instructions of the program further for identifying users that have rated each other high and low, and using these identifications in conjunction with an estimate of how similar one user is to the other to derive ratings as estimates of how the users will rate other users that they have not yet rated;

wherein recommending comprises scoring user-prospect matches to indicate quality of match between respective prospects and users, wherein the scores are derived from weighting plural matched attribute information of the prospects to the users'"'"' desired-prospect attributes.

14. The apparatus of claim 13, the instructions of the program further for obtaining the ratings from a fourth plurality of the users.

15. The apparatus of claim 13, the instructions of the program further for obtaining the ratings by estimating which users are most like other users based on users having similar ratings of other users.

16. The apparatus of claim 13, the instructions of the program further for providing to a fifth plurality of the users respective preliminary lists of prospects, and obtaining from the fifth plurality of users each user'"'"'s rating of the prospects in the user'"'"'s respective preliminary list,

wherein the ratings reflect the user'"'"'s opinion of a quality of match of the prospects in the preliminary list,

wherein the fifth plurality of the users comprises a subset of the first plurality of users, the second plurality of users and the third plurality of the users.

17. The apparatus of claim 13, the instructions of the program further for, if a prospect is deemed to be a potential match for a given user based on a combination of proximity data and other data, then evaluating whether the prospect'"'"'s attributes match the user'"'"'s desired-attributes.

18. The apparatus of claim 13 wherein recommending further comprises categorizing the prospects.

19. The apparatus of claim 18 wherein the categories are selected from the group consisting of dating, friendship, activities, networking, deal making and reuniting.

20. The apparatus of claim 13 wherein at least some of the users rate other users.

21. The apparatus of claim 13 wherein recommending further comprises scoring matches of users and prospects.

22. The apparatus of claim 13, the instructions of the program further for adjusting the scores based on the attributes of the prospect being rated.

23. The apparatus of claim 22, the instructions of the program further for adjusting the scores based on the ratings.

24. The apparatus of claim 13, the instructions of the program further for invalidating ratings by a given user if the given user has a pattern of ratings which fail to correlate to ratings by other users.

25. The apparatus of claim 13 further comprising a user input device, a display device, and a processor.