articleJan 1, 2006Closed access

Local Graph Partitioning using PageRank Vectors

University of California, San Diego · University of California, Berkeley · +1 more institution

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Abstract

A local graph partitioning algorithm finds a cut near a specified starting vertex, with a running time that depends largely on the size of the small side of the cut, rather than the size of the input graph. In this paper, we present a local partitioning algorithm using a variation of PageRank with a specified starting distribution. We derive a mixing result for PageRank vectors similar to that for random walks, and show that the ordering of the vertices produced by a PageRank vector reveals a cut with small conductance. In particular, we show that for any set C with conductance Phi and volume k, a PageRank vector with a certain starting distribution can be used to produce a set with conductance (O(radic(Phi…

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Authors

3

Topics & keywords

Keywords
  • PageRank
  • Vertex (graph theory)
  • Combinatorics
  • Random walk
  • Set (abstract data type)
  • Graph
  • Conductance
  • Distribution (mathematics)
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