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Conference papers

Using Grammar-Based Genetic Programming for Mining Disjointness Axioms Involving Complex Class Expressions

Thu Huong Nguyen 1 Andrea G. B. Tettamanzi 1
1 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
Abstract : In the context of the Semantic Web, learning implicit knowledge in terms of axioms from Linked Open Data has been the object of much current research. In this paper, we propose a method based on grammar-based genetic programming to automatically discover disjoint-ness axioms between concepts from the Web of Data. A training-testing model is also implemented to overcome the lack of benchmarks and comparable research. The acquisition of axioms is performed on a small sample of DBpedia with the help of a Grammatical Evolution algorithm. The accuracy evaluation of mined axioms is carried out on the whole DBpe-dia. Experimental results show that the proposed method gives high accuracy in mining class disjointness axioms involving complex expressions .
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Submitted on : Friday, September 11, 2020 - 9:46:04 AM
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Thu Huong Nguyen, Andrea G. B. Tettamanzi. Using Grammar-Based Genetic Programming for Mining Disjointness Axioms Involving Complex Class Expressions. ICCS 2020 - 25th International Conference on Conceptual Structures, Sep 2020, Bozen-Bolzano, Italy. pp.18-32, ⟨10.1007/978-3-030-57855-8_2⟩. ⟨hal-02936193⟩

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