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Using Domain Knowledge to Guide Lattice-based Complex Data Exploration

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 propose an approach which combines semantic resources and formal concept analysis to deal with heterogenous data sets represented as many-valued (MV) formal contexts. We define a new Galois connection considering the semantic relationships between attribute values in a MV context. The semantic relationships are used to calculate the similarity between attribute values to decide whether an attribute is shared by a set of objects or not. Then, based on this Galois connection, we define MV formal concepts and MV concept lattices. Depending on a chosen similarity threshold, MV concept lattices may have different levels of precision. We take advantage of this feature to browse the content of a biological databases repository in a dynamic and progressive way. The browsing process combines the navigation in several MV concept lattices and allows zooming operations by switching between MV concept lattices with higher or lower precision.
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Submitted on : Friday, December 10, 2010 - 3:00:30 PM
Last modification on : Thursday, April 28, 2022 - 3:11:30 AM




Nizar Messai, Marie-Dominique Devignes, Amedeo Napoli, Malika Smaïl-Tabbone. Using Domain Knowledge to Guide Lattice-based Complex Data Exploration. 19th European Conference on Artificial Intelligence - ECAI 2010, Aug 2010, Lisbon, Portugal. pp.847--852, ⟨10.3233/978-1-60750-606-5-847⟩. ⟨inria-00545545⟩



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