Effective ranking and recommendation on web page retrieval by integrating association mining and PageRank

Ja Hwung Su*, Bo Wen Wang, Vincent Shin-Mu Tseng

*Corresponding author for this work

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

9 Scopus citations

Abstract

Nowadays, the well-known search engines, such as Google, Yahoo, MSN, etc, have provided the users with good search results based on special search strategies. However there still exist some problems unsolved for traditional search engines, including: 1) the gap between user's intention and searched results is not easy to narrow down under the global search space, and 2) user's interested pages hidden in the local website are not associated with the search results. To deal with such problems, in this paper, we propose a novel approach for personalized page ranking and recommendation by integrating association mining and PageRank so as to meet user's search goals. Moreover, by mining the users' browsing behaviors, we can successfully bridge the gap between global search results and local preferences. The effectiveness of our proposed approach was verified through experimental evaluations.

Original languageEnglish
Title of host publicationProceedings - 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2008
Pages455-458
Number of pages4
DOIs
StatePublished - 1 Dec 2008
Event2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2008 - Sydney, NSW, Australia
Duration: 9 Dec 200812 Dec 2008

Publication series

NameProceedings - 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2008

Conference

Conference2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2008
CountryAustralia
CitySydney, NSW
Period9/12/0812/12/08

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