Using pattern structures to support information retrieval with Formal Concept Analysis

Victor Codocedo 1 Ioanna Lykourentzou 1 Hernan Astudillo 2 Amedeo Napoli 1
1 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : In this paper we introduce a novel approach to information retrieval (IR) based on Formal Concept Analysis (FCA). The use of concept lattices to support the task of document retrieval in IR has proven effective since they allow querying in the space of terms modelled by concept intents and navigation in the space of documents modelled by concept extents. However, current approaches use binary representations to illustrate the relations between documents and terms (''document D contains term T'') and disregard useful information present in document corpora (''document D contains X references to term T''). We propose using pattern structures, an extension of FCA on multi-valued and numerical data, to address the above. Given a set of weighted document-term relations, a concept lattice based on pattern structures is built and explored to find documents satisfying a given user query. We present the meaning and capabilities of this approach, as well as results of its application over a classic IR document corpus.
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https://hal.inria.fr/hal-00880020
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Victor Codocedo, Ioanna Lykourentzou, Hernan Astudillo, Amedeo Napoli. Using pattern structures to support information retrieval with Formal Concept Analysis. International Workshop "What can FCA do for Artificial Intelligence?", Aug 2013, Beijing, China. pp.15-24. ⟨hal-00880020⟩

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