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Using SiteRank for Decentralized Computation of Web Document Ranking
 

Summary: Using SiteRank for Decentralized Computation
of Web Document Ranking
Jie Wu and Karl Aberer
School of Computer and Communication Sciences
Swiss Federal Institute of Technology (EPF), Lausanne
1015 Lausanne, Switzerland
{jie.wu,karl.aberer}@epfl.ch
Abstract. The PageRank algorithm demonstrates the significance of the compu-
tation of document ranking of general importance or authority in Web informa-
tion retrieval. However, doing a PageRank computation for the whole Web graph
is both time-consuming and costly. State of the art Web crawler based search
engines also suffer from the latency in retrieving a complete Web graph for the
computation of PageRank. We look into the problem of computing PageRank
in a decentralized and timely fashion by making use of SiteRank and aggregat-
ing rankings from multiple sites. A SiteRank is basically the ranking generated
by applying the classical PageRank algorithm to the graph of Web sites, i.e., the
Web graph at the granularity of Web sites instead of Web pages. Our empirical re-
sults show that SiteRank also follows a power-law distribution. Our experimental
results demonstrate that the decomposition of global Web document ranking com-
putation by making use of SiteRank is a very promising approach for computing

  

Source: Aberer, Karl - Faculté Informatique et Communications, Ecole Polytechnique Fédérale de Lausanne

 

Collections: Computer Technologies and Information Sciences