SEMI-SUPERVISED IDENTITY AGGREGATION OF PROFILES USING STATISTICAL METHODS

• US 20140074928A1
• Filed: 07/01/2013
• Published: 03/13/2014
• Est. Priority Date: 09/10/2012
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: B'FAR, REZA, SPAULDING, KENT, CENGIZ, YASIN, KAL, YENAL, CAVES, AMERICO, GOH, FUN, LINGG, ELIZABETH, SHI, YEMIN, FU, CHENGXIAO
• Granted Patent: US 9,654,594 B2
• Time in Patent Office: Days
• US Class Current: 709/204
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 63/102 Entity profiles
• CPC Class Codes: H04L 63/20 for managing network security; network security policies in general filtering policies H04L63/0227
• CPC Class Codes: H04L 67/306 User profiles

Abstract

User profiles can be analyzed to identify profiles matching to the same identity. For example, profiles from different social network systems are analyzed to determine if the profiles are associated with the same user of the social network systems. Multiple heuristics may be calculated using different algorithms. The calculated heuristics may then be combined to generate a match score that indicates whether two profiles match.

Claims

1. A method for aggregating social network profiles, the method comprising:

accessing data of a first profile from a first data source;

accessing data of a second profile from a second data source;

determining whether the second profile is identified by the first profile;

in response to determining that the second profile is identified by the first profile, identifying the second profile as matching the first profile;

in response to determining that the second profile is not identified by the first profile calculating one or more heuristics and determining whether the first profile and the second profile match based on the calculated one or more heuristics.

2. The method of claim 1, wherein calculating one or more heuristics comprises:

obtaining attributes of the first profile;

generating attributes of the second profile;

identifying attributes of the second profile matching attributes of the first profile; and

calculating a heuristic based at least in part on the identified matching attributes.

3. The method of claim 1, wherein calculating one or more heuristics comprises:

obtaining one or more expressions of interest from the first profile;

obtaining one or more expressions of interest from the second profile;

identifying expressions of interest from the second profile matching expressions of interest from the first profile; and

calculating a heuristic based at least in part on the identified matching expressions of interest.

4. The method of claim 1, wherein calculating one or more heuristics comprises:

obtaining one or more profile connections from the first profile;

obtaining one or more profile connections from the second profile;

identifying profile connections from the second profile matching profile connections from the first profile; and

calculating a heuristic based at least in part on the identified matching profile connections.

5. The method of claim 1, wherein calculating one or more heuristics comprises:

obtaining one or more images associated with the first profile;

obtaining one or more images associated with the second profile;

identifying faces within the obtained images associated with the first profile and the images associated with the second profile;

identifying images associated with the second profile matching images associated with the first profile based on the identified faces; and

calculating a heuristic based at least in part on the identified matching images.

6. The method of claim 1, wherein calculating one or more heuristics comprises:

obtaining content posted in connection with the first profile;

obtaining content posted in connection with the second profile;

identifying content posted in connection with the first profile that at least partially matches content posted in connection with the second profile;

calculating a number of instances of at least partially matching content that is posted to both the first profile and the second profile within a time threshold; and

calculating a heuristic based at least in part on the calculated number of instances.

7. The method of claim 1, wherein calculating one or more heuristics comprises:

obtaining a set of hyperlinks posted in connection with the first profile;

obtaining a set of hyperlinks posted in connection with the second profile;

identifying hyperlinks posted in connection with the first profile that at least partially matches hyperlinks posted in connection with the second profile;

calculating a number of matching hyperlinks that are posted to both the first profile and the second profile; and

calculating a heuristic based at least in part on the calculated number of matching hyperlinks.

8. A system comprising:

a processor; and

a memory coupled with and readable by the processor and storing therein a set of instructions which, when executed by the processor, causes the processor to aggregate social network profiles by;

accessing data of a first profile from a first data source;

accessing data of a second profile from a second data source;

determining whether the second profile is identified by the first profile;

in response to determining that the second profile is identified by the first profile, identifying the second profile as matching the first profile;

in response to determining that the second profile is not identified by the first profile calculating one or more heuristics and determining whether the first profile and the second profile match based on the calculated one or more heuristics.

9. The system of claim 8, wherein calculating one or more heuristics comprises:

obtaining attributes of the first profile;

generating attributes of the second profile;

identifying attributes of the second profile matching attributes of the first profile; and

calculating a heuristic based at least in part on the identified matching attributes.

10. The system of claim 8, wherein calculating one or more heuristics comprises:

obtaining one or more expressions of interest from the first profile;

obtaining one or more expressions of interest from the second profile;

identifying expressions of interest from the second profile matching expressions of interest from the first profile; and

calculating a heuristic based at least in part on the identified matching expressions of interest.

11. The system of claim 8, wherein calculating one or more heuristics comprises:

obtaining one or more profile connections from the first profile;

obtaining one or more profile connections from the second profile;

identifying profile connections from the second profile matching profile connections from the first profile; and

calculating a heuristic based at least in part on the identified matching profile connections.

12. The system of claim 8, wherein calculating one or more heuristics comprises:

obtaining one or more images associated with the first profile;

obtaining one or more images associated with the second profile;

identifying faces within the obtained images associated with the first profile and the images associated with the second profile;

identifying images associated with the second profile matching images associated with the first profile based on the identified faces; and

calculating a heuristic based at least in part on the identified matching images.

13. The system of claim 8, wherein calculating one or more heuristics comprises:

obtaining content posted in connection with the first profile;

obtaining content posted in connection with the second profile;

identifying content posted in connection with the first profile that at least partially matches content posted in connection with the second profile;

calculating a number of instances of at least partially matching content that is posted to both the first profile and the second profile within a time threshold; and

calculating a heuristic based at least in part on the calculated number of instances.

14. The system of claim 8, wherein calculating one or more heuristics comprises:

obtaining a set of hyperlinks posted in connection with the first profile;

obtaining a set of hyperlinks posted in connection with the second profile;

identifying hyperlinks posted in connection with the first profile that at least partially matches hyperlinks posted in connection with the second profile;

calculating a number of matching hyperlinks that are posted to both the first profile and the second profile; and

calculating a heuristic based at least in part on the calculated number of matching hyperlinks.

15. A computer-readable memory comprising a set of instructions stored therein which, when executed by a processor, causes the processor to aggregate social network profiles by:

accessing data of a first profile from a first data source;

accessing data of a second profile from a second data source;

determining whether the second profile is identified by the first profile;

in response to determining that the second profile is identified by the first profile, identifying the second profile as matching the first profile;

in response to determining that the second profile is not identified by the first profile calculating one or more heuristics and determining whether the first profile and the second profile match based on the calculated one or more heuristics.

16. The method of claim 15, wherein calculating one or more heuristics comprises:

obtaining attributes of the first profile;

generating attributes of the second profile;

identifying attributes of the second profile matching attributes of the first profile; and

calculating a heuristic based at least in part on the identified matching attributes.

17. The computer-readable memory of claim 15, wherein calculating one or more heuristics comprises:

obtaining one or more expressions of interest from the first profile;

obtaining one or more expressions of interest from the second profile;

identifying expressions of interest from the second profile matching expressions of interest from the first profile; and

calculating a heuristic based at least in part on the identified matching expressions of interest.

18. The computer-readable memory of claim 15, wherein calculating one or more heuristics comprises:

obtaining one or more profile connections from the first profile;

obtaining one or more profile connections from the second profile;

identifying profile connections from the second profile matching profile connections from the first profile; and

calculating a heuristic based at least in part on the identified matching profile connections.

19. The computer-readable memory of claim 15, wherein calculating one or more heuristics comprises:

obtaining one or more images associated with the first profile;

obtaining one or more images associated with the second profile;

identifying faces within the obtained images associated with the first profile and the images associated with the second profile;

identifying images associated with the second profile matching images associated with the first profile based on the identified faces; and

calculating a heuristic based at least in part on the identified matching images.

20. The computer-readable memory of claim 15, wherein calculating one or more heuristics comprises:

obtaining content posted in connection with the first profile;

obtaining content posted in connection with the second profile;

identifying content posted in connection with the first profile that at least partially matches content posted in connection with the second profile;

calculating a number of instances of at least partially matching content that is posted to both the first profile and the second profile within a time threshold; and

calculating a heuristic based at least in part on the calculated number of instances.