Automatic thematic categorization of documents using a fuzzy taxonomy and fuzzy hierarchical clustering

Wallace, M; Akrivas, G; Stamou, G

dc.contributor.author	Wallace, M	en
dc.contributor.author	Akrivas, G	en
dc.contributor.author	Stamou, G	en
dc.date.accessioned	2014-03-01T02:42:12Z
dc.date.available	2014-03-01T02:42:12Z
dc.date.issued	2003	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30860
dc.subject	Automatic Detection	en
dc.subject	Hierarchical Clustering	en
dc.subject	Semantic Indexing	en
dc.subject	Similarity Measure	en
dc.subject.other	Hierarchical systems	en
dc.subject.other	Indexing (of information)	en
dc.subject.other	Problem solving	en
dc.subject.other	Semantics	en
dc.subject.other	Automatic thematic categorization	en
dc.subject.other	Fuzzy control	en
dc.title	Automatic thematic categorization of documents using a fuzzy taxonomy and fuzzy hierarchical clustering	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/FUZZ.2003.1206644	en
heal.identifier.secondary	http://dx.doi.org/10.1109/FUZZ.2003.1206644	en
heal.publicationDate	2003	en
heal.abstract	In this paper we formally define the problem of automatic detection of thematic categories in a semantically indexed document, and identify the main obstacles to overcome in this process. Furthermore, we explain how detection of thematic categories can be achieved, with the use of a fuzzy quasi-taxonomic relation. Our approach relies on a fuzzy hierarchical clustering algorithm; this algorithm uses a similarity measure that is based on the notion of context.	en
heal.journalName	IEEE International Conference on Fuzzy Systems	en
dc.identifier.doi	10.1109/FUZZ.2003.1206644	en
dc.identifier.volume	2	en
dc.identifier.spage	1446	en
dc.identifier.epage	1451	en