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

Nguyen, Thu Huong; Tettamanzi, Andrea G. B.

doi:10.1007/978-3-030-57855-8_2

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…Using the SHOIQ description logic syntax, the notation C ⊑ D highlights the inclusion of C into D, i.e. the fact that instances of C are also instances of D. This is described in the direct model-theoretic semantics of OWL through the notation C I ⊆ D I where I represents individuals in a knowledge Our research area focuses on Axiom Learning [9], which is a bottom-up approach, using learning algorithms and relying on instances from several existing knowledge and information resources to discover axioms. Axiom learning algorithms can help reduce the overall cost of axiom extraction and ontology construction in general.…”

Section: Preliminaries a Owl Subclassof Axiomsmentioning

confidence: 99%

“…To this aim, we adopt am axiom evaluation heuristic, based on possibility theory [11], which has been shown to be particularly reliable in view of the openworld semantics of RDF knowledge graphs [13]. The heuristic computes a possibility and a necessity for a given axiom; some particular cases, like the DisjointClasses axiom, require a slightly different treatment, whereby their necessity is always zero and only their possibility is computed [8], [9].…”

Section: Preliminaries a Owl Subclassof Axiomsmentioning

confidence: 99%

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Optimizing the Computation of a Possibilistic Heuristic to Test OWL SubClassOf Axioms Against RDF Data

Felin

Corby

Faron-Zucker

et al. 2022

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)

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The growth of the semantic Web requires tools to manage data, make them available to humans and for a wide range of applications. In particular, tools dedicated to ontology management are a keystone for semantic Web applications. In this paper we consider a possibilistic framework and an evolutionary approach for ontology enrichment with OWL axioms. The assessment of candidate OWL axioms against an RDF knowledge graph requires a high computational cost, especially in terms of computation time (CPU), which may limit the applicability of the framework. To answer this problem, our contribution presented in this paper consists of (i) a multi-threading system to parallelize axiom assessment, (ii) a heuristic to avoid redundant computation and (iii) an optimization for SPARQL query chunking relying on an extension of the SPARQL 1.1 Federated Query standard. The results of a comparative evaluation show that our proposal significantly outperforms the original algorithm, enabling a significant reduction in computation time.

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Section: Preliminaries a Owl Subclassof Axiomsmentioning

confidence: 99%

Section: Preliminaries a Owl Subclassof Axiomsmentioning

confidence: 99%

Optimizing the Computation of a Possibilistic Heuristic to Test OWL SubClassOf Axioms Against RDF Data

Felin

Corby

Faron-Zucker

et al. 2022

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)

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A Multi-Objective Evolutionary Approach to Class Disjointness Axiom Discovery

Nguyen

Tettamanzi

2020

2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)

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The huge wealth of linked data available on the Web (also known as the Web of data), organized according to the standards of the Semantic Web, can be exploited to automatically discover new knowledge, expressed in the form of axioms, one of the essential components of ontologies. In order to overcome the limitations of existing methods for axiom discovery, we propose a two-objective grammar-based genetic programming approach that casts axiom discovery as a genetic programming problem involving the two independent criteria of axiom credibility and generality. We demonstrate the power of the proposed approach by applying it to the task of discovering class disjointness axioms involving complex class expression, a type of axioms that plays an important role in improving the quality of ontologies. We carry out experiments to determine the most appropriate parameter settings and we perform an empirical comparison of the proposed method with state-of-the-art methods proposed in the literature.

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

Felin

Tettamanzi

2021

IEEE/WIC/ACM International Conference on Web Intelligence

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Ontology enrichment is a key task in the area of the Semantic Web. It allows directly to enrich the links between entities of the semantic Web and thus adding information. Our research area is part of this objective with the search for axioms using an evolutionary process. We propose an adaptation resulting from the coupling between evolutionary algorithms and the theory of possibilities in order to allow the research of axioms of subsumption composed of complex classes.

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

Cited by 3 publications

References 16 publications

Optimizing the Computation of a Possibilistic Heuristic to Test OWL SubClassOf Axioms Against RDF Data

Optimizing the Computation of a Possibilistic Heuristic to Test OWL SubClassOf Axioms Against RDF Data

A Multi-Objective Evolutionary Approach to Class Disjointness Axiom Discovery

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

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