Many-Valued Concept Lattices for Conceptual Clustering and Information Retrieval

Nizar Messai 1 Marie-Dominique Devignes 1 Amedeo Napoli 1 Malika Smaïl-Tabbone 1
1 ORPAILLEUR - Knowledge representation, reasonning
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : In this paper we present an extension of the Galois connection to deal with many-valued formal contexts. We define a many-valued Galois connection with respect to similarity between attribute values in a many-valued context. Then, we define many-valued formal concepts and many-valued concept lattices. Depending on a similarity threshold, many-valued concept lattices may have different levels of precision. This feature makes them very useful for multilevel conceptual clustering. Many-valued concept lattices are also used in a new lattice-based information retrieval approach for efficiently answering complex queries.
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Conference papers
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https://hal.inria.fr/inria-00338671
Contributor : Malika Smail-Tabbone <>
Submitted on : Thursday, November 13, 2008 - 11:15:38 PM
Last modification on : Thursday, January 11, 2018 - 6:19:54 AM

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Nizar Messai, Marie-Dominique Devignes, Amedeo Napoli, Malika Smaïl-Tabbone. Many-Valued Concept Lattices for Conceptual Clustering and Information Retrieval. 18th European Conference in Artificial Intelligence - ECAI 2008, Jul 2008, Patras, Greece. pp.127-131. ⟨inria-00338671⟩

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