Trust propagation through both explicit and implicit social networks

• US 20060294134A1
• Filed: 08/02/2006
• Published: 12/28/2006
• Est. Priority Date: 06/28/2005
• Status: Active Grant

• Current Assignee: R2 Solutions LLC (Acacia Research Corporation)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Taha, Abe, Berkhim, Pavel, Rose, Daniel E., Xu, Zhichen, Maghoul, Farzin, Mao, Jianchang
• Granted Patent: US 8,442,978 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/313 Selection or weighting of terms for indexing
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: Y10S 707/99932 Access augmentation or optimizing
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching

Abstract

The present invention is directed towards systems and methods for trust propagation. The method according to one embodiment comprises calculating a first feature vector for a first user, calculating a second feature for a second user and comparing the first feature vector with the second feature vector to calculate a similarity value. A determination is made as to whether the similarity value falls within a threshold. If the similarity value falls within the threshold, a relationship is recorded between the first user and the second user in a first user profile and a second user profile.

Claims

1. A method for propagating trust to create an implicit social network, the method comprising:

calculating a first feature vector for a first user;

calculating a second feature for a second user;

comparing the first feature vector with the second feature vector to calculate a similarity value;

determining whether the similarity value falls within a threshold; and

if the similarity value falls within the threshold, recording a relationship between the first user and the second user in a first user profile and a second user profile.

2. The method of claim 1 wherein calculating the first feature vector comprises calculating on the basis of an annotation by the first user for a content item.

3. The method of claim 1 wherein calculating the first feature vector comprises calculating on the basis of a tag by the first user for a content item.

4. The method of claim 1 wherein calculating the first feature vector comprises calculating on the basis of a save by the first user of a content item.

5. The method of claim 1 wherein determining comprises determining if the first user and the second user are related in accordance with an implicit social network.

6. The method of claim 1 wherein comparing comprises determining one or more items of personalized information in common between the first feature vector and the second feature vector.

7. The method of claim 6 wherein determining comprises determining if the first feature vector indicates that the first user saved a content item and the second feature vector indicates that the second user saved the content item.

8. the method of claim 6 wherein determining comprises determining if the first feature vector indicates that the first user tagged a content item and the second feature vector indicates that the second user tagged the content item.

9. The method of claim 6 wherein determining comprises determining if the firs feature vector indicates that the first user annotated a content item and the second feature vector indicates that the second user annotated the content item.

10. The method of claim 1 comprising:

calculating a third feature for a third user;

comparing the first feature vector with the third feature vector to calculate a similarity value;

determining whether the similarity value falls within a threshold; and

if the similarity value falls within the threshold, recording a relationship between the first user and the third user in the first user profile and a third user profile.

11. The method of claim 10 wherein determining comprises determining if the first user and the third user a related in accordance with an implicit social network.

12. A method for propagating trust to create an implicit social network, the method comprising:

means for calculating a first feature vector for a first user;

means for calculating a second feature for a second user;

means for comparing the first feature vector with the second feature vector to calculate a similarity value;

means for determining whether the similarity value falls within a threshold; and

if the similarity value falls within the threshold, means for recording a relationship between the first user and the second user in a first user profile and a second user profile.