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dc.contributor.authorPoelmans, Jonas
dc.contributor.authorElzinga, Paul
dc.contributor.authorViaene, Stijn
dc.contributor.authorDedene, Guido (+)
dc.contributor.authorKuznetsov, Sergei O.
dc.date.accessioned2017-12-02T14:42:11Z
dc.date.available2017-12-02T14:42:11Z
dc.date.issued2011
dc.identifier.doi10.1007/978-3-642-31488-9_22
dc.identifier.urihttp://hdl.handle.net/20.500.12127/4122
dc.description.abstractFormal Concept Analysis (FCA) is an unsupervised clustering technique and many scientific papers are devoted to applying FCA in Information Retrieval (IR) research. We collected 103 papers published between 2003-2009 which mention FCA and information retrieval in the abstract, title or keywords. Using a prototype of our FCA-based toolset CORDIET, we converted the pdf-files containing the papers to plain text, indexed them with Lucene using a thesaurus containing terms related to FCA research and then created the concept lattice shown in this paper. We visualized, analyzed and explored the literature with concept lattices and discovered multiple interesting research streams in IR of which we give an extensive overview. The core contributions of this paper are the innovative application of FCA to the text mining of scientific papers and the survey of the FCA-based IR research.
dc.language.isoen
dc.subjectInformation Retrieval
dc.subjectConcept Lattice
dc.subjectQuery Enlargement
dc.subjectInformation Retrieval System
dc.titleText mining scientific papers: A survey on FCA-based information retrieval research
vlerick.conferencedate30/08/2011-03/09/2011
vlerick.conferencelocationNew York, United States
vlerick.conferencenameIndustrial Conference on Data Mining
vlerick.knowledgedomainOperations & Supply Chain Management
vlerick.typeconfpresConference Proceeding
vlerick.vlerickdepartmentTOM
dc.identifier.vperid51528
dc.identifier.vperid140610
dc.identifier.vperid144578
dc.identifier.vperid141017
dc.identifier.vperid76321
dc.identifier.vpubid4757


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