Refining web search engine results using incremental clustering

Authors:
Ya-Jun Zhang;Zhi-Qiang Liu
Affiliations:
Department of Computer Science and Software Engineering, The University of Melbourne, VIC 3010, Australia;Department of Computer Science and Software Engineering, The University of Melbourne, VIC 3010, Australia and School of Creative Media, City University of Hong Kong, Kowloon, Hong Kong, P. R. Chin ...
Venue:
International Journal of Intelligent Systems - Intelligent Technologies
Year:
2004

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Abstract

In this article, we present a new solution to improve the Web search performance. Our algorithm is based on a new clustering algorithm that classifies the results of a query from a search engine into subgroups and assigns each group a short series of keywords together with some statistics data. Then, the user may look into the group with the keywords that he/she finds interesting. Compared with the approaches available in the literature, our algorithm does not require the number of groups as the prior knowledge; it starts from a single prototype group and adaptively expands the prototype set based on a self-spawning splitting scheme until all the groups are finally identified. © 2004 Wiley Periodicals, Inc.