Wang YT, Kitsuregawa M "Use Link-based Clustering to Improve Web Search Results"

[Eugene Garfield]

kitsure at tkl.iis.u-tokyo.ac.jp


Title     Use Link-based Clustering to Improve Web Search Results
Author    Yitong Wang and Masaru Kitsuregawa
          The University of Tokyo
Source    Proceedings of the 2nd International Conference on
          Web Information Systems Engineering (WISE'01)

Members who have access to IEEE Computer Society can access the article at :

http://dlib2.computer.org/conferen/wise/1393/pdf/volume1/13930115.pdf


Abstract  While web search engine could 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. In this
paper, we propose a new link-based clustering approach to cluster search
results returned from Web search engine 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 standard clustering algorithm,
K-means, to make it more natural to handle noises 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.

Keywords: link analysis, co-citation, coupling, hub, authority

Proceedings of the 2nd International Conference on Web Information Systems
Engineering (WISE'01)
Copyright (c) 2002 Institute of Electrical and Electronics Engineers, Inc.
All rights reserved.