NDLI: Use link-based clustering to improve Web search results

Content Provider	IEEE Xplore Digital Library
Author	Yitong Wang Kitsuregawa, M.
Copyright Year	2001
Description	Author affiliation: Inst. of Ind. Sci., Tokyo Univ., Japan (Yitong Wang; Kitsuregawa, M.)
Abstract	While Web search engines can retrieve information on the Web for a specific topic, users have to step a long ordered list in order to locate the needed information, which is often tedious and less efficient. We propose a new link-based clustering approach to cluster search results returned from Web search engines by exploring both co-citation and coupling. Unlike document clustering algorithms in IR that are based on common words/phrases shared among documents, our approach is based on common links shared by pages. We also extend the standard clustering algorithm, K-means, to make it more natural to handle noise and apply it to Web search results. By filtering some irrelevant pages, our approach clusters high quality pages in Web search results into semantically meaningful groups to facilitate users accessing and browsing. Preliminary experiments and evaluations are conducted to investigate its effectiveness. The experimental results show that link-based clustering of Web search results is promising and beneficial.
Starting Page	115
Ending Page	124
File Size	875966
Page Count	10
File Format	PDF
ISBN	076951393X
DOI	10.1109/WISE.2001.996472
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-12-03
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Web search Web pages Search engines Clustering algorithms Information retrieval Information filtering Information filters Internet Data engineering Data mining
Content Type	Text
Resource Type	Article

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