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An FCA Framework for Knowledge Discovery in SPARQL Query Answers

Melisachew Wudage Chekol 1 Amedeo Napoli 1 
1 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : Formal concept analysis (FCA) is used for knowledge discovery within data. In FCA, concept lattices are very good tools for classification and organization of data. Hence, they can also be used to visualize the answers of a SPARQL query instead of the usual answer formats such as: RDF/XML, JSON, CSV, and HTML. Consequently, in this work, we apply FCA to reveal and visualize hidden relations within SPARQL query answers by means of concept lattices.
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Submitted on : Thursday, November 7, 2013 - 2:28:06 PM
Last modification on : Thursday, August 4, 2022 - 5:18:44 PM
Long-term archiving on: : Monday, February 10, 2014 - 11:35:56 AM


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  • HAL Id : hal-00881080, version 1


Melisachew Wudage Chekol, Amedeo Napoli. An FCA Framework for Knowledge Discovery in SPARQL Query Answers. The 12th International Semantic Web Conference, Oct 2013, Sydney, Australia. ⟨hal-00881080⟩



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