BEATCA swMATH ID: 8281 Software Authors: Ciesielski, Krzysztof; Czerski, Dariusz; Dramiński, Michał; Kłopotek, Mieczysław A.; Wierzchoń; Sławomir T. Description: Semantic information within the BEATCA framework In this paper we investigate the impact of semantic information on the quality of hierarchical, fuzzy-based clustering of a collection of textual documents. We show that via a relevant tagging of a part of the documents one can improve the quality of overall clustering, both of tagged and un-tagged documents. Homepage: http://matwbn.icm.edu.pl/ksiazki/cc/cc39/cc3925.pdf Keywords: semantic information; clustering with partial multilabel supervision Related Software: Cited in: 0 Publications