Refining web search engine results using incremental clustering

  1. Ya-Jun Zhang1,
  2. Zhi-Qiang Liu1,2,*

Article first published online: 12 JAN 2004

DOI: 10.1002/int.10161

Issue

International Journal of Intelligent Systems

International Journal of Intelligent Systems

Special Issue: Intelligent Technologies

Volume 19, Issue 1-2, pages 191–199, January - February 2004

Additional Information

How to Cite

Zhang, Y.-J. and Liu, Z.-Q. (2004), Refining web search engine results using incremental clustering. Int. J. Intell. Syst., 19: 191–199. doi: 10.1002/int.10161

Author Information

  1. 1

    Department of Computer Science and Software Engineering, The University of Melbourne, VIC 3010, Australia

  2. 2

    School of Creative Media, City University of Hong Kong, Kowloon, Hong Kong, P. R. China

*Department of Computer Science and Software Engineering, The University of Melbourne, VIC 3010, Australia

Publication History

  1. Issue published online: 12 JAN 2004
  2. Article first published online: 12 JAN 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.

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