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Exploring Web Search Results Clustering

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNChapter (peer-reviewed)peer-review

Published
  • Xiaoxia Wang
  • Max Bramer
  • Frans Coenen (Editor)
  • Andrew Tuson (Editor)
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Publication date2007
Host publicationResearch and Development in Intelligent Systems XXIII: Proceedings of AI-2006, the Twenty-sixth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence
PublisherIEEE
Pages393-397
Number of pages5
ISBN (Electronic)9781846286636
ISBN (Print)9781846286629
<mark>Original language</mark>English

Abstract

As the number of documents on the web has proliferated, the low precision of conventional web search engines and the flat ranked search results presentation make it difficult for users to locate specific information of interest. Grouping web search results into a hierarchy of topics provides an alternative to the flat ranked list and facilitates searching and browsing. In this paper, we present a brief survey of previous work on web search results clustering and existing commercial search engines using this technique, discuss two key issues of web search results clustering: cluster summarisation and evaluation and propose some directions for future research.