Query-specific clustering of search results based on document-context similarity scores

Authors:
E. K. F. Dang;R. W. P. Luk;D. L. Lee;K. S. Ho;S. C. F. Chan
Affiliations:
University, Hung Hom, Hong Kong;University, Hung Hom, Hong Kong;Hong Kong University of Science & Technology, Hong Kong;University, Hung Hom, Hong Kong;University, Hung Hom, Hong Kong
Venue:
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Year:
2006

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Abstract

This paper presents a pilot study of query-specific clustering that uses our novel document-context based similarity scores as compared with document similarity scores. Clustering is applied to the top 1000 retrieved documents for a given query. Clustering effectiveness is evaluated based on the MK1 score for TREC-2, TREC-6 and TREC-7 test collections. Encouraging results were obtained whereby document-context clustering produces better MK1 scores than document clustering with a 95% confidence level if precision and recall are equally important.