Paper Info
Title
Effective Ranking and Recommendation on Web Page Retrieval by Integrating Association Mining and PageRank
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 userpsilas intention and searched results is not easy to narrow down under the global search space, and (2) userpsilas 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 userpsilas search goals. Moreover, by mining the userspsila 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.
Year
DOI
Venue
2008
10.1109/WIIAT.2008.49
Web Intelligence/IAT Workshops
Keywords
Field
DocType
effective ranking,global search result,web page retrieval,well-known search engine,good search result,special search strategy,information retrieval,recommendation,traditional search engine,browsing behaviors,local preference,personalized page ranking,association mining,web sites,local website,pagerank,global search space,data mining,search result,integrating association mining,search engines,search strategies,search space,search engine,navigation,web pages,ensemble
Web search engine,Data mining,PageRank,Organic search,Metasearch engine,World Wide Web,Information retrieval,Semantic search,Computer science,Search engine optimization,Search analytics,Spamdexing
Conference
Volume
ISBN
Citations 
3
978-0-7695-3496-1
4
PageRank 
References 
Authors
0.40
5
3
Name
Order
Citations
PageRank
Ja-Hwung Su132924.53
Bo-Wen Wang2663.58
Vincent S. Tseng32923161.33