Abstrakt
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.