Trust propagation through both explicit and implicit social networks

Patent metadata

Field	Value
Publication number	US-9576029-B2
Application number	US-201313859208-A
Country	US
Kind code	B2
Filing date	Apr 9, 2013
Priority date	Jun 28, 2005
Publication date	Feb 21, 2017
Grant date	Feb 21, 2017

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.

First claim

We claim:

1. A method implemented on a machine having at least one processor, storage, and a communication platform capable of connecting to a network for propagating trust to create an implicit social network, comprising:
obtaining a content item;
receiving a first user profile including information about a first set of activities of a first user with respect to the content item;
receiving a second user profile including information about a second set of activities of a second user with respect to the content item;
determining a similarity between the first user and the second user based on the first and the second sets of activities with respect to the content item; and
generating an implicit relationship between the first user and the second user when the similarity with respect to the content item exceeds a threshold, wherein a ranking of a second content item determined based on the second user profile and an evaluation of the second user from other users implicitly related to the second user is to be used, based on the implicit relationship, to rank the second content item in a search result provided to the first user.

2. The method of claim 1 , further comprising:
calculating a first feature vector for the first user based on the first user profile; and
calculating a second feature vector for the second user based on the second user profile.

3. The method of claim 2 , wherein
calculating the first feature vector comprises calculating on the basis of a tag by the first user for the content item, and
calculating the first feature vector comprises calculating on the basis of a save by the first user of the content item.

4. The method of claim 2 , wherein the first feature vector indicates that the first user saved the content item and the second feature vector indicates that the second user saved the content item.

5. The method of claim 2 , wherein the first feature vector indicates that the first user tagged the content item and the second feature vector indicates that the second user tagged the content item.

6. The method of claim 2 , comprising:
calculating a third feature vector for a third user;
comparing the first feature vector with the third feature vector to calculate a similarity value;
recording a relationship between the first user and the third user in the first user profile and a third user profile based upon the similarity value, wherein the similarity value exceeds the threshold;
retrieving the third user profile based on the recorded relationship between the first user and the third user, wherein both the second user profile and the third user profile can be used to rank search results provided to the first user.

7. The method of claim 6 , wherein determining comprises determining if the first user and the third user are related in accordance with an implicit social network.

8. 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.

9. A method implemented on a machine having at least one processor, storage, and a communication platform capable of connecting to a network for propagating trust to create an implicit social network, comprising:
obtaining a content item;
receiving a first user profile including information about a first set of activities of a first user with respect to the content item, wherein the first set of activities includes an annotation from the first user with respect to the content item;
receiving a second user profile including information about a second set of activities of a second user with respect to the content item, wherein the second set of activities includes an annotation from the second user with respect to the content item;
determining a similarity between the first user and the second user based on the first and the second sets of activities;
generating an implicit relationship between the first user and the second user when the similarity exceeds a threshold;
in response to a search request by the first user, determining a search result set that includes the content item;
ranking the search result set based on the second user profile when the similarity exceeds a threshold, wherein the ranking comprises:
determining a trust value for the second user based on the second user profile, wherein the trust value indicates a degree of trust with respect to the second user by one or more users each of which has an implicit relationship with the second user,
obtaining a rating of the content item by the second user, and
determining a rank of the content item in the search result set based on a product of the trust value and the rating; and

providing the ranked search result set to the first user.

Assignees

• Yahoo Inc
• Excalibur Ip Llc

Inventors

• Berkhim Pavel
• Xu Zhichen
• Mao Jianchang
• Rose Daniel E
• Taha Abe
• Maghoul Farzin

Classifications

• Y10S707/99932

  Access augmentation or optimizing · CPC title

• G06F17/30867

  Physics · mapped topic

• G06F17/30616

  Physics · mapped topic

• G06F17/3053 Primary

  Physics · mapped topic

• Y10S707/99933

  Query processing, i.e. searching · CPC title