A cooccurrence-based thesaurus and two applications to information retrieval
Information Processing and Management: an International Journal
Web document clustering: a feasibility demonstration
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Foundations of statistical natural language processing
Foundations of statistical natural language processing
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ACM Transactions on Information Systems (TOIS)
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Optimizing the number of search result categories
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Mining search engine query logs for query recommendation
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Automatic thesaurus construction based on grammatical relations
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IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
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EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
Improving quality of search results clustering with approximate matrix factorisations
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
Clustering search results for mobile terminals
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
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Search results clustering is useful for clarifying vague queries and in managing the sheer volume of web pages. But these clusters are often incomprehensible to users. In this paper, we propose a new method for producing intuitive clusters that greatly aid in finding desired web search results. By using terms that are both frequently used in queries and found together on web pages to build clusters our method combines the better features of both "computer-oriented clustering" and "humanoriented clustering". Our evaluation experiments show that this method provides the user with appropriate clusters and clear labels.