Sri International

Google Inc.

Sugato Basu

Jeffrey Eric Davitz

Jiye Yu

David Gutelius

Mehran Sahami

Taher H Haveliwala

Glen M Jeh

Sepandar D Kamvar

Bilgehan Uygar Oztekin

Tessa Macduff

Mark Drummond

Mikhail Bilenko

In one embodiment, the present invention is a method and apparatus for knowledge generation and deployment in a distributed network. In one embodiment, a method for processing messages in a social network includes receiving a new message from a first node in the network, the new message including a query, providing the first node with an answer to the query, if the answer is located in a repository, and initiating generation of the answer, if the answer is not located in the repository.

Method and apparatus for processing messages in a social network

In a method of generating a search boost vector, a first set of content location identifiers for first content are provided. A second set of content location identifiers for second content are identified. The second content is related to the first content in accordance with one or more predefined criteria. A search boost vector is generated by determining weights corresponding to content location identifiers in the second set of content location identifiers. The search boost vector may also be generated by determining weights corresponding to content location identifiers in the first set of content location identifiers. The predefined criteria may include one or more additional content location identifiers that are co-visited with one or more content location identifiers for the first set of content location identifiers. Co-visits are by a community of users during an interval of time.

Search boost vector based on co-visitation information

A method and apparatus for targeting messages to users in a social network, for example by first identifying topics in the social network is provided. One embodiment of a method for discovering topics in a social network includes collecting information from the social network, the information including at least one of: interactions between users of the social network or profile information for the users, determining a global topic model including at least one topic, based on the collected information, and locally refining the global topic model in accordance with the collected information.

Method and apparatus for targeting messages to users in a social network

A method and system to produce and train composite similarity functions for record linkage problems, including product normalization problems, is disclosed. In one embodiment, for a group of products in a plurality of products, a composite similarity function is constructed for the group of products from a weighted set of basis similarity functions. Training records are used to calculate the weights in the weighted set of basis similarity functions in the composite similarity function for the group of products. In another embodiment, a composite similarity function is applied to pairs of training records. The application of the composite similarity function provides a number that can be used to indicate whether two records relate to a common subject. The composite similarity function includes a weighted set of basis similarity functions. A perceptron algorithm is used to modify the weights in the weighted set.

Method and system to produce and train composite similarity functions for product normalization

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Redwood City, CA, United States of America

Sugato Basu