Exploiting wikipedia knowledge for conceptual hierarchical clustering of documents

Spanakis, G; Siolas, G; Stafylopatis, A

dc.contributor.author	Spanakis, G	en
dc.contributor.author	Siolas, G	en
dc.contributor.author	Stafylopatis, A	en
dc.date.accessioned	2014-03-01T02:08:59Z
dc.date.available	2014-03-01T02:08:59Z
dc.date.issued	2012	en
dc.identifier.issn	00104620	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/29761
dc.subject	conceptual clustering	en
dc.subject	document clustering	en
dc.subject	document representation	en
dc.subject	Wikipedia knowledge	en
dc.subject.other	Application programmer's interfaces	en
dc.subject.other	Bag-of-words models	en
dc.subject.other	Clustering process	en
dc.subject.other	Computational costs	en
dc.subject.other	Conceptual clustering	en
dc.subject.other	Document Clustering	en
dc.subject.other	Document Representation	en
dc.subject.other	F-measure	en
dc.subject.other	Hier-archical clustering	en
dc.subject.other	Link structure	en
dc.subject.other	Textual content	en
dc.subject.other	Wikipedia	en
dc.subject.other	Clustering algorithms	en
dc.subject.other	Knowledge representation	en
dc.subject.other	Semantics	en
dc.subject.other	Websites	en
dc.title	Exploiting wikipedia knowledge for conceptual hierarchical clustering of documents	en
heal.type	journalArticle	en
heal.identifier.primary	10.1093/comjnl/bxr024	en
heal.identifier.secondary	http://dx.doi.org/10.1093/comjnl/bxr024	en
heal.publicationDate	2012	en
heal.abstract	In this paper, we propose a novel method for conceptual hierarchical clustering of documents using knowledge extracted from Wikipedia. The proposed method overcomes the classic bag-of-words models disadvantages through the exploitation of Wikipedia textual content and link structure. A robust and compact document representation is built in real-time using the Wikipedia application programmer's interface, without the need to store locally any Wikipedia information. The clustering process is hierarchical and extends the idea of frequent items by using Wikipedia article titles for selecting cluster labels that are descriptive and important for the examined corpus. Experiments show that the proposed technique greatly improves over the baseline approach, both in terms of F-measure and entropy on the one hand and computational cost on the other. © 2011 The Author. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.	en
heal.journalName	Computer Journal	en
dc.identifier.doi	10.1093/comjnl/bxr024	en
dc.identifier.volume	55	en
dc.identifier.issue	3	en
dc.identifier.spage	299	en
dc.identifier.epage	312	en