Reexamining the cluster hypothesis: scatter/gather on retrieval results
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Web document clustering: a feasibility demonstration
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Grouper: a dynamic clustering interface to Web search results
WWW '99 Proceedings of the eighth international conference on World Wide Web
Modern Information Retrieval
Document Ranking and the Vector-Space Model
IEEE Software
Mining topic-specific concepts and definitions on the web
WWW '03 Proceedings of the 12th international conference on World Wide Web
Learning to cluster web search results
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Efficient Phrase-Based Document Indexing for Web Document Clustering
IEEE Transactions on Knowledge and Data Engineering
A new suffix tree similarity measure for document clustering
Proceedings of the 16th international conference on World Wide Web
Web Document Clustering Technique Using Case Grammar Structure
ICCIMA '07 Proceedings of the International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007) - Volume 02
Introduction to Information Retrieval
Introduction to Information Retrieval
International Journal of Information Retrieval Research
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The World Wide Web is a large distributed digital information space. The ability to search and retrieve information from the Web efficiently and effectively is an enabling technology for realizing its full potential. Information Retrieval IR plays an important role in search engines. Today's most advanced engines use the keyword-based "bag of words" paradigm, which has inherent disadvantages. Organizing web search results into clusters facilitates the user's quick browsing of search results. Traditional clustering techniques are inadequate because they do not generate clusters with highly readable names. This paper proposes an approach for web search results in clustering based on a phrase based clustering algorithm. It is an alternative to a single ordered result of search engines. This approach presents a list of clusters to the user. Experimental results verify the method s feasibility and effectiveness.