BASSET: scalable gateway finder in large graphs

  • Authors:
  • Hanghang Tong;Spiros Papadimitriou;Christos Faloutsos;Philip S. Yu;Tina Eliassi-Rad

  • Affiliations:
  • Carnegie Mellon University;IBM T.J Watson;Carnegie Mellon University;University of Illinois at Chicago;Lawrence Livermore National Laboratory

  • Venue:
  • PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
  • Year:
  • 2010

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Abstract

Given a social network, who is the best person to introduce you to, say, Chris Ferguson, the poker champion? Or, given a network of people and skills, who is the best person to help you learn about, say, wavelets? The goal is to find a small group of ‘gateways': persons who is close enough to us, as well as close enough to the target (person, or skill) or, in other words, are crucial in connecting us to the target. The main contributions are the following: (a) we show how to formulate this problem precisely; (b) we show that it is sub-modular and thus it can be solved near-optimally; (c) we give fast, scalable algorithms to find such gateways Experiments on real data sets validate the effectiveness and efficiency of the proposed methods, achieving up to 6,000,000x speedup.