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Fuzzy Logic and Ontology-based Information Retrieval

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Fuzzy Logic

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 215))

Abstract

Most of information retrieval (IR) approaches relies on the hypothesis that keywords extracted from a document are sufficient to evaluate the relevance of that document with respect to the query. Such an approach may insufficiently lay bare the semantic contents of the documents. In addition to keywords, automatic indexing methods need external knowledge such as thesauri and ontologies for improving the representation of documents or for expanding queries to related keywords. Moreover, ontologies may be combined with a view of for estimating the relevance of documents, the “proximity” between words, or for expressing flexible queries. In this chapter, we survey several recent approaches. Then, two types of methods are discussed in detail. The first one uses a symbolic pattern matching approach, which is based on possibilistic ontologies (where qualitative necessity and possibility degrees estimate to what extent two terms refer to the same thing). The second type of approaches projects fuzzy set representations of queries and documents on a classical ontology, and compare these projections for rank ordering the documents according to a retrieval status value.

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Authors
  1. Mustapha Baziz
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  2. Mohand Boughanem
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  3. Yannick Loiseau
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  4. Henri Prade
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Editor information

Editors and Affiliations

  1. Department of Electrical & Computer Engineering, Pratt School of Engineering Duke University, Science Drive, West Campus, 27708 Durham, N. C, USA

    Paul P. Wang

  2. The Belgian Nuclear Research Centre (SCK ·CEN), Boeretang 200, 2400 Mol, Belgium

    Da Ruan

  3. Department of Applied Mathematics & Computer Science, Ghent University, Krijgslaan 281 (S9), 9000 Gent, Belgium

    Etienne E. Kerre

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Baziz, M., Boughanem, M., Loiseau, Y., Prade, H. (2007). Fuzzy Logic and Ontology-based Information Retrieval. In: Wang, P.P., Ruan, D., Kerre, E.E. (eds) Fuzzy Logic. Studies in Fuzziness and Soft Computing, vol 215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71258-9_10

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  • DOI: https://doi.org/10.1007/978-3-540-71258-9_10

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