Browse > Article

C-rank: A Contribution-Based Approach for Web Page Ranking  

Lee, Sang-Chul (한양대학교 전자컴퓨터통신공학과)
Kim, Dong-Jin ((주)NHN)
Son, Ho-Yong (한양대학교 전자컴퓨터통신공학과)
Kim, Sang-Wook (한양대학교 정보통신학부)
Lee, Jae-Bum ((주)NHN)
Abstract
In the past decade, various search engines have been developed to retrieve web pages that web surfers want to find from world wide web. In search engines, one of the most important functions is to evaluate and rank web pages for a given web surfer query. The prior algorithms using hyperlink information like PageRank incur the problem of 'topic drift'. To solve the problem, relevance propagation models have been proposed. However, these models suffer from serious performance degradation, and thus cannot be employed in real search engines. In this paper, we propose a new ranking algorithm that alleviates the topic drift problem and also provides efficient performance. Through a variety of experiments, we verify the superiority of the proposed algorithm over prior ones.
Keywords
Web Page Ranking; Relevance Propagation;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Dong-Jin Kim, C-rank: A Contribution-Based Web Page Ranking Algorithm, NHN Internal Technical Report, TR-NHN-2007-158, 2007. (In Korean)
2 Lucene, http://lucene.apache.org.
3 TREC Web Track, http://es.cmis.csiro.au/TRECWeb.
4 R. Baeza-Yates and B. Ribeiro-Neto, Modern Information Retrieval, Addision-Wesley, 1999.
5 P. Lawrence et al., The PageRank Citation Ranking: Bringing Order to the Web, Technical Report, Stanford University, 1998.
6 M. Richardson and P. Domingos, "The Intelligent Surfer: Probabilistic Combination of Link and Content Information In PageRank," In Advances in Neural Information Processing Systems 14, pp.1141-1448, 2002.
7 A. Shakery and C. Zhai, "A Probabilistic Relevance Propagation Model for Hypertext Retrieval," In Proc. ACM Int'l. Conf. on Information and Knowledge Management, pp.550-558, 2006.
8 S. E. Robertson, "Overview of the Okapi projects," Journal of Documentation, vol.53, no.1, pp.3-7, 1997.   DOI   ScienceOn
9 S. Chakrabarti, Mining The Web, Morgan Kaufmann, 2002.
10 T. Qin et al., "A Study of Relevance Propagation of Web Search," In Proc. ACM Int'l. Conf. on Information Retrieval, pp.408-415, 2005.
11 J. M. Kleinberg, "Authoritative Sources in a Hyperlinked Environment," Journal of the ACM, vol.46, no.5, pp.604-632, 1999.   DOI   ScienceOn