Bridging DBpedia Categories and DL-Concept Definitions using Formal Concept Analysis

Mehwish Alam 1 Aleksey Buzmakov 1 Victor Codocedo 1 Amedeo Napoli 1
1 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : The popularization and quick growth of Linked Open Data (LOD) has led to challenging aspects regarding quality assessment and data exploration of the RDF triples that shape the LOD cloud. Particularly, we are interested in the completeness of data and its potential to provide concept definitions in terms of necessary and sufficient conditions. In this work we propose a novel technique based on Formal Concept Analysis which organizes RDF data into a concept lattice. This allows the discovery of implications, which are used to automatically detect missing information and then to complete RDF data.
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Communication dans un congrès
Proceedings of the 4th International Workshop "What can FCA do for Artificial Intelligence?", FCA4AI 2015, co-located with the International Joint Conference on Artificial Intelligence (IJCAI 2015), Buenos Aires, Argentina., Jul 2015, Buenos Aires, Argentina. 1430, 2015, CEUR Workshop Proceedings
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Mehwish Alam, Aleksey Buzmakov, Victor Codocedo, Amedeo Napoli. Bridging DBpedia Categories and DL-Concept Definitions using Formal Concept Analysis. Proceedings of the 4th International Workshop "What can FCA do for Artificial Intelligence?", FCA4AI 2015, co-located with the International Joint Conference on Artificial Intelligence (IJCAI 2015), Buenos Aires, Argentina., Jul 2015, Buenos Aires, Argentina. 1430, 2015, CEUR Workshop Proceedings. 〈hal-01186330〉

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