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Effectively finding relevant web pages from linkage information

Hou, Jingyu and Zhang, Yanchun 2003, Effectively finding relevant web pages from linkage information, IEEE transactions on knowledge and data engineering, vol. 15, no. 4, pp. 940-951.

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Title Effectively finding relevant web pages from linkage information
Author(s) Hou, Jingyu
Zhang, Yanchun
Journal name IEEE transactions on knowledge and data engineering
Volume number 15
Issue number 4
Start page 940
End page 951
Publisher Institue of Electrical and Electronics Engineers Inc.
Place of publication New York, N.Y.
Publication date 2003-07
ISSN 1041-4347
1558-2191
Keyword(s) World Wide Web
Web search
information retrieval
hyperlink analysis
singular value decomposition (SVD)
Summary This paper presents two hyperlink analysis-based algorithms to find relevant pages for a given Web page (URL). The first algorithm comes from the extended cocitation analysis of the Web pages. It is intuitive and easy to implement. The second one takes advantage of linear algebra theories to reveal deeper relationships among the Web pages and to identify relevant pages more precisely and effectively. The experimental results show the feasibility and effectiveness of the algorithms. These algorithms could be used for various Web applications, such as enhancing Web search. The ideas and techniques in this work would be helpful to other Web-related researches.
Language eng
Field of Research 080799 Library and Information Studies not elsewhere classified
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ┬ęThis material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30002037

Document type: Journal Article
Collections: School of Information Technology
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