Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Affinity rank: a new scheme for efficient web search
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
An optimized k-means algorithm of reducing cluster intra-dissimilarity for document clustering
WAIM'05 Proceedings of the 6th international conference on Advances in Web-Age Information Management
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This contribution describes clustering of most informative keywords within full-text query results and its visualization in 2D or 3D space using so-called sociomapping. The main goal of the clustering is to help user with orientation in the term space and with the reformulating --- more detail specification --- of ambiguous queries. Test data were obtained from web search engines like Yahoo!, Google etc. To be able to evaluate quality of the used clustering method we have used 2 metrics to compare it with manually classified collection (Reuters Corpus Volume 1), moreover, the quality of preserving mutual distances of clusters from original multi-dimensional space was measured by Spearman's rank correlation coefficient.