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    Text mining scientific papers: A survey on FCA-based information retrieval research

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    Publication type
    Conference Proceeding
    Author
    Poelmans, Jonas
    Elzinga, Paul
    Viaene, Stijn
    Dedene, Guido (+)
    Kuznetsov, Sergei O.
    Publication Year
    2011
    
    Metadata
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    Abstract
    Formal 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.
    Keyword
    Information Retrieval, Concept Lattice, Query Enlargement, Information Retrieval System
    Knowledge Domain/Industry
    Operations & Supply Chain Management
    DOI
    10.1007/978-3-642-31488-9_22
    URI
    http://hdl.handle.net/20.500.12127/4122
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-3-642-31488-9_22
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