Xuanhui Wang
ABSTRACT
PageRank has been known to be a successful algorithm in ranking web sources. In order to avoid the rank sink problem, PageRank assumes that a surfer, being in a page, jumps to a random page with a certain probability. In the standard PageRank algorithm, the jumping probabilities are assumed to be the same for all the pages, regardless of the page properties. This is not the case in the real world, since presumably a surfer would more likely follow the out-links of a high-quality hub page than follow the links of a low-quality one. In this poster, we propose a novel algorithm "Dirichlet PageRank" to address this problem by adapting exible jumping probabilities based on the number of out-links in a page. Empirical results on TREC data show that our method outperforms the standard PageRank algorithm.
- S. Brin and L. Page. The anatomy of a large-scale hypertextual web search engine. Computer Networks, 30(1-7):107--117, 1998. Google Scholar
Digital Library
- D. Cai, X. He, J.-R. Wen, and W.-Y. Ma. Block-level link analysis. In SIGIR, pages 440--447, 2004. Google ScholarDigital Library
- J. M. Kleinberg. Authoritative sources in a hyperlinked environment. J. ACM, 46(5):604--632, 1999. Google ScholarDigital Library
- C. Zhai and J. D. Lafferty. A study of smoothing methods for language models applied to ad hoc information retrieval. In SIGIR, pages 334--342, 2001. Google ScholarDigital Library
Index Terms
- Dirichlet PageRank
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