Local methods for estimating PageRank Values

Yen Yu Chen, Qingqing Gan, Torsten Suel

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    The Google search engine uses a method called PageRank, together with term-based and other ranking techniques, to order search results returned to the user. PageRank uses link analysis to assign a global importance score to each web page. The PageRank scores of all the pages are usually determined off-line in a large-scale computation on the entire hyperlink graph of the web, and several recent studies have focused on improving the efficiency of this computation, which may require multiple hours on a typical workstation. However, in some scenarios, such as online analysis of link evolution and mining of large web archives, it may be desirable to quickly approximate or update the PageRanks of individual nodes without performing a large-scale computation on the entire graph. We address this problem by studying several methods for efficiently estimating the PageRank score of a particular web page using only a small subgraph of the entire web.

    Original languageEnglish (US)
    Title of host publicationCEUR Workshop Proceedings
    Pages14-23
    Number of pages10
    Volume703
    StatePublished - 2004
    Event3rd International Workshop on Web Dynamics, WebDyn 2004, in Conjunction with the 13th International World Wide Web Conference - New York, NY, United States
    Duration: May 18 2004May 18 2004

    Other

    Other3rd International Workshop on Web Dynamics, WebDyn 2004, in Conjunction with the 13th International World Wide Web Conference
    CountryUnited States
    CityNew York, NY
    Period5/18/045/18/04

    ASJC Scopus subject areas

    • Computer Science(all)

    Fingerprint Dive into the research topics of 'Local methods for estimating PageRank Values'. Together they form a unique fingerprint.

  • Cite this

    Chen, Y. Y., Gan, Q., & Suel, T. (2004). Local methods for estimating PageRank Values. In CEUR Workshop Proceedings (Vol. 703, pp. 14-23)