A semantic approach to concept lattice-based information retrieval

Victor Codocedo 1 Ioanna Lykourentzou 2, 1 Amedeo Napoli 1
1 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : The volume of available information is growing, especially on the web, and in parallel the questions of the users are changing and becoming harder to satisfy. Thus there is a need for organizing the available information in a meaningful way in order to guide and improve document indexing for information retrieval applications taking into account more complex data such as semantic relations. In this paper we show that Formal Concept Analysis (FCA) and concept lattices provide a suitable and powerful support for such a task. Accordingly, we use FCA to compute a concept lattice, which is considered both a semantic index to organize documents and a search space to model terms. We introduce the notions of cousin concepts and classification-based reasoning for navigating the concept lattice and retrieve relevant information based on the content of concepts. Finally, we detail a real-world experiment and show that the present approach has very good capabilities for semantic indexing and document retrieval.
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Victor Codocedo, Ioanna Lykourentzou, Amedeo Napoli. A semantic approach to concept lattice-based information retrieval. Annals of Mathematics and Artificial Intelligence, Springer Verlag, 2014, 72, pp.169 - 195. ⟨10.1007/s10472-014-9403-0⟩. ⟨hal-01095859⟩

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