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Enhanced searching algorithms for relevant web pages using hyperlink graphs

Published: 18 March 2005 Publication History

Abstract

This paper explores the behavior of four graph-based search algorithms that use only the hyperlink structure of the web to identify related and relevant web pages. These four algorithms that are based on similarity analysis of the pages are combined with a new way to construct the page graph source. We compare their performance with the Companion algorithm graph-based search algorithm. Experimental results show the advantages of these four algorithms.

References

[1]
Dean, J. and Henzinger, M. R. Finding related web pages in the World Wide Web. Proc. 8th International World Wide Web Conference (WWW8), 1999, 389--401.
[2]
Kleinberg, J. M. Authoritative sources in a hyperlinked environment. Journal of the ACM 46, no. 5, 1999, 604--632.
[3]
Gibson, D., Kleinberg, J. M., and Raghavan, P. Inferring web communities from link topology. UK Conference on Hypertext, 1998, 225--234.
[4]
Grossman, J. P. Recursive node similarity in networked information spaces, Proc. Innovative Internet Community Systems, Leipzig, German, 2003.
[5]
Lu, W., Janssen, J., Milios, E., and Japkowicz, N., Node similarity in networked information spaces, Proc. CASCON 2001.

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Published In

cover image ACM Conferences
ACMSE '05 vol 1: Proceedings of the 43rd annual ACM Southeast Conference - Volume 1
March 2005
408 pages
ISBN:1595930590
DOI:10.1145/1167350
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 March 2005

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Author Tags

  1. HITS
  2. authorities
  3. hubs
  4. link analysis
  5. similarity measure

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ACM SE05
Sponsor:
ACM SE05: ACM Southeast Regional Conference 2005
March 18 - 20, 2005
Georgia, Kennesaw

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Overall Acceptance Rate 502 of 1,023 submissions, 49%

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