<rdf:RDF xmlns:community="http://www.bibsonomy.org/ontologies/2008/05/community#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:admin="http://webns.net/mvcb/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:syn="http://purl.org/rss/1.0/modules/syndication/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns:cc="http://web.resource.org/cc/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" xmlns:swrc="http://swrc.ontoware.org/ontology#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xml:base="http://www.bibsonomy.org/user/renew/clustering"><owl:Ontology rdf:about=""><rdfs:comment>BibSonomy publications for /user/renew/clustering</rdfs:comment><owl:imports rdf:resource="http://swrc.ontoware.org/ontology/portal"/></owl:Ontology><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/2bbdcaeb1167d2eec89427b07b510605c/renew"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/2bbdcaeb1167d2eec89427b07b510605c/renew"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Article"/><owl:sameAs rdf:resource="http://dx.doi.org/10.1007/978-3-540-72665-4_41"/><swrc:date>Fri Feb 22 23:58:23 CET 2008</swrc:date><swrc:journal>Advances in Artificial Intelligence</swrc:journal><swrc:pages>476--488</swrc:pages><swrc:title>Fuzzy Clustering for Topic Analysis and Summarization of Document Collections</swrc:title><swrc:year>2007</swrc:year><swrc:keywords>summarization fuzzy clustering </swrc:keywords><swrc:abstract>Large document collections, such as those delivered by Internet search engines, are difficult and time-consuming for users
to read and analyse. The detection of common and distinctive topics within a document set, together with the generation ofmulti-document summaries, can greatly ease the burden of information management. We show how this can be achieved with a clusteringalgorithm based on fuzzy set theory, which (i) is easy to implement and integrate into a personal information system, (ii)generates a highly flexible data structure for topic analysis and summarization, and (iii) also delivers excellent performance.</swrc:abstract><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="René Witte"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Sabine Bergler"/></rdf:_2></rdf:Seq></swrc:author></rdf:Description></rdf:RDF>