The PowerRank Web Link Analysis Algorithm

  • Yizhou Lu ,
  • Benyu Zhang ,
  • Wensi Xi ,
  • Zheng Chen ,
  • Yi Liu ,
  • Michael R. Lyu ,
  • Wei-Ying Ma

13th international conference on World Wide Web |

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The web graph follows the power law distribution and has a
hierarchy structure. But neither the PageRank algorithm nor any
of its improvements leverage these attributes. In this paper, we
propose a novel link analysis algorithm “the PowerRank
algorithm”, which makes use of the power law distribution
attribute and the hierarchy structure of the web graph. The
algorithm consists two parts. In the first part, special treatment is
applied to the web pages with low “importance” score. In the
second part, the global “importance” score for each web page is
obtained by combining those scores together. Our experimental
results show that: 1) The PowerRank algorithm computes
10%~30% faster than PageRank algorithm. 2) Top web pages in
PowerRank algorithm remain similar to that of the PageRank
algorithm.