Microsoft Technology Licensing, LLC

Yahoo! Inc.

Bahman Bahmani

Shanmugasundaram Ravikumar

Kaushik Chakrabarti

Sergei Vassilvitskii

Dong Xin

Methods and systems for generating a dense graph are described. One of the methods includes receiving a graph and computing a threshold to apply to the graph. The method further includes determining whether the graph includes a first set of at least one node, determining whether a second set of at least one node from the first set meets the threshold, and removing the at least one node of the second set concurrently from the graph upon determining that the at least one node of the second set meets the threshold. The operation of removing is performed to generate an updated graph. The method includes determining whether a density of the updated graph is greater than a density of the graph and replacing the graph within the updated graph upon determining that the density of the updated graph is greater than the density of the density of the graph.

Systems and methods for generating a dense graph

A personalized page rank computation system is described herein that provides a fast MapReduce method for Monte Carlo approximation of personalized PageRank vectors of all the nodes in a graph. The method presented is both faster and less computationally intensive than existing methods, allowing a broader scope of problems to be solved by existing computing hardware. The system adopts the Monte Carlo approach and provides a method to compute single random walks of a given length for all nodes in a graph that it is superior in terms of the number of map-reduce iterations among a broad class of methods. The resulting solution reduces the I/O cost and outperforms the state-of-the-art FPPR approximation methods, in terms of efficiency and approximation error. Thus, the system can very efficiently perform single random walks of a given length starting at each node in the graph and can very efficiently approximate all the personalized PageRank vectors.

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Stanford, CA, United States of America

Bahman Bahmani