TRUST PROPAGATION THROUGH BOTH EXPLICIT AND IMPLICIT SOCIAL NETWORKS
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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.
139 Citations
22 Claims
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1-12. -12. (canceled)
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13. A method for propagating trust to create an implicit social network, comprising:
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storing a content item in an inverted index; receiving profile information from at least one user, the profile information relating to actions by the user to the content item including an annotation submitted by the user for the content item, the annotation including descriptive text generated b the user; recording the profile information to a stream search queue when an update threshold is not exceeded, whether the update threshold is exceeded determined based on a last update of the inverted index; storing the contents of the stream queue to the inverted index when the update threshold is exceeded; calculating a first feature vector for a first user based on first user profile information; calculating a second feature for a second feature vector for a second user based on second user profile information; calculating a similarity value using the first feature vector and the second feature vector indicating if the actions by the first user to the content item are similar to the actions by the second user to the content item; when the similarity value fails within a feature threshold, recording a relationship between the first user and the second user in a first user profile and a second user profile, the feature threshold based in part on features used to calculate the first feature vector and the second feature vector; in response to a search request by the first user, determining a search result set, the search result set includes the content item, and profile information in the inverted index and the stream search queue; and ranking the search result set based on the second user profile information related to actions by the second user to the content item when the similarity value falls within the features threshold. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22)
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Specification