Yahoo! Inc.

Excalibur IP, LLC

R2 Solutions, LLC

Tamas Sarlos

Kunal Punera

Theodoros Lappas

Shanmugasundaram Ravikumar

Jan O Pedersen

Jon Degenhardt

Anirban Dasgupta

Tapas Kanungo

Descriptive data relating to at least a subset of a plurality of entities on a website is retrieved over a network. Endorsement data relating to the plurality of entities is retrieved from the website. A first set of probabilities is determined reflecting a probability that endorsements can be attributed to specific aspects. A second set of probabilities is determined reflecting a probability that terms can be attributed to aspects. Using the first set of probabilities and the second set of probabilities, a subset of the terms that are most probably associated with each entity are selected. Tags are then generated for each entity using the selected terms.

Computerized system and method for determining non-redundant tags from a user's network activity

System and method for mining tags using social endorsement networks

The subject matter disclosed herein relates to generating an abstract of an electronic document based at least in part on a utility metric associated with a group phrases as well as on a ranked order of sentences.

Generation of search result abstracts

Disclosed are apparatus and methods for compressing a set of numerical values for a set of feature values, which can be utilized by a rule based or decision tree system. In certain embodiments, the numerical values are transformed into a subset of integer values based on how they are to be analyzed by conditional processes of the rule based or decision tree system that compare such numerical values to one or more threshold values. This transformation is accomplished such that if the rule based or decision tree system is applied after transformation, identical results are produced as compared to the original numerical values being used by the rule based or decision tree system. Other compression techniques may also be applied to the transformed values. An altered rule based or decision tree system, in which threshold values are also transformed to integer values, may be applied to the transformed values. Alternatively, the rule based or decision tree system may be applied to a set of decoded numerical values.

Apparatus and methods for lossless compression of numerical attributes in rule based systems

Method, system, and programs for computing similarity. Input data is first received from one or more data sources and then analyzed to obtain an input feature vector that characterizes the input data. An index is then generated based on the input feature vector and is used to archive the input data, where the value of the index is computed based on an improved Johnson-Lindenstrass transformation (FJLT) process. With the improved FJLT process, first, the sign of each feature in the input feature vector is randomly flipped to obtain a flipped vector. A Hadamard transformation is then applied to the flipped vector to obtain a transformed vector. An inner product between the transformed vector and a sparse vector is then computed to obtain a base vector, based on which the value of the index is determined.

Method and system for fast similarity computation in high dimensional space

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Sunnyvale, CA, United States of America

Tamas Sarlos