ABSTRACT
PageRank is defined as the stationary state of a Markov chain depending on a damping factor α that spreads uniformly part of the rank. The choice of α is eminently empirical, and in most cases the original suggestion α=0.85 by Brin and Page is still used. It is common belief that values of α closer to 1 give a "truer to the web" PageRank, but a small α accelerates convergence. Recently, however, it has been shown that when α=1 all pages in the core component are very likely to have rank 0 [1]. This behaviour makes it difficult to understand PageRank when α≈1, as it converges to a meaningless value for most pages. We propose a simple and natural modification to the standard preprocessing performed on the adjacency matrix of the graph, resulting in a ranking scheme we call TruRank. TruRank ranks the web with principles almost identical to PageRank, but it gives meaningful values also when α☰ 1.
- {1} Paolo Boldi, Massimo Santini, and Sebastiano Vigna. PageRank as a function of the damping factor. In Proc. of the Fourteenth International World Wide Web Conference, Chiba, Japan, 2005. ACM Press. Google Scholar
Digital Library
- {2} Lawrence Page, Sergey Brin, Rajeev Motwani, and Terry Winograd. The PageRank citation ranking: Bringing order to the web. Technical report, Stanford Digital Library Technologies Project, Stanford University, Stanford, CA, USA, 1998.Google Scholar
Index Terms
TruRank: taking PageRank to the limit
Recommendations
PageRank as a function of the damping factor
WWW '05: Proceedings of the 14th international conference on World Wide WebPageRank is defined as the stationary state of a Markov chain. The chain is obtained by perturbing the transition matrix induced by a web graph with a damping factor α that spreads uniformly part of the rank. The choice of α is eminently empirical, and ...
Topic-Sensitive PageRank: A Context-Sensitive Ranking Algorithm for Web Search
The original PageRank algorithm for improving the ranking of search-query results computes a single vector, using the link structure of the Web, to capture the relative “importance” of Web pages, independent of any particular search query. To yield more ...
Topic-sensitive PageRank
WWW '02: Proceedings of the 11th international conference on World Wide WebIn the original PageRank algorithm for improving the ranking of search-query results, a single PageRank vector is computed, using the link structure of the Web, to capture the relative "importance" of Web pages, independent of any particular search ...





Comments