Columbia University

International Business Machines Corporation

Bert Huang

Tony Jebara

Arun Hampapur

Yada Zhu

Blake Shaw

Lexing Xie

A method, system, computer program product and computer readable media for matching using degree distribution information are disclosed. An embodiment of the method can include performing b-matching on a graph data structure expanded using degree distribution information in order to identify neighbors of a selected input node. The b-matching can be performed using belief propagation. The belief propagation method is adapted to use a compressed message update rule and to be suitable for use with distributed processing systems. An embodiment can also include enhancing a matching result by applying degree distribution information to a first matching result to generate a second matching result. Embodiments for online advertisement/search term matching, product recommendation, dating service and social network matching, auction buyer/seller matching and resource allocation, among other, are disclosed.

Machine optimization devices, methods, and systems

Entities may be matched to enhance the efficiency of various commercial activities using various system and method embodiments of the disclosed subject matter. Belief propagation on a graph data structure defining a bipartite or unipartite matching opportunity is used to calculate a best matching. In embodiments, functions are implemented based upon the match, such as executing sales between matched buyers and sellers in an online auction system. In embodiments, messages with scalar values carry information about the relative value of possible matchings, initially provided as weights or values for the possible matchings. Weights may depend on, for example, bids or costs. Messages may be passed, for example over a network between processors respective to the nodes. Belief values reflecting a best matching can be continuously updated for each node responsively to the value information and received messages to rank the matches respective to each node, which progressively improve. This allows short or complete terminations conditions to determine the goodness of the matching. Differing numbers of matches respective to each member of the disjoint sets and distributions of the desirability of different numbers of matches can be integrated in the matchings in respective embodiments.

Belief propagation for generalized matching

Methods and systems for predicting links in a network, such as a social network, are disclosed. The existing network structure can be used to optimize link prediction. The methods and systems can learn a distance metric and/or a degree preference function that are structure preserving to predict links for new/existing nodes based on node properties.

Network information methods devices and systems

Principles of the invention provide techniques for analyzing spatiotemporally ambiguous events. In one aspect, an exemplary method includes the steps of storing event data representative of an event, the event data comprising spatiotemporally ambiguous measurements; storing side information, the side information comprising at least one of spatial data and temporal data related to the event in space-time: associating the event data with the side information by soft association to form association data; applying one or more estimation techniques to the association data to form estimation data; and determining at least one of a rate, a factor, a likelihood, a value, a time, a location, and a cause for the event by applying one or more characterization techniques to the estimation data.

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New York, NY, United States of America

Bert Huang