Modular Ontologies Composition: Levenshtein-Distance-Based Concepts Structure Comparison

Modular Ontologies Composition: Levenshtein-Distance-Based Concepts Structure Comparison

Hanen Abbes (MIRACL Laboratory, Higher Institute of Computer Science and Multimedia, Sfax University, Sfax, Tunisia) and Faïez Gargouri (MIRACL Laboratory, Higher Institute of Computer Science and Multimedia, Sfax University, Sfax, Tunisia)
DOI: 10.4018/IJITWE.2018100103

Abstract

This article describes how a modular ontology is a set of interconnected ontology modules. Modularity is a key requirement for collaborative ontology engineering and for distributed ontology reuse on the Web. Combining ontology modules in this context to get a global ontology is an important issue since it requires to resolves mismatches between the compared concepts. This article proposes a novel approach to automatically compose ontology modules. The proposed approach is based on concept structure comparison. The algorithm allowing to merge the ontology modules into a global ontology is detailed and similarity measures are explained. Similarity measures are computed against concept names, attributes and relationships. Experiments performed to test this algorithm are described and evaluation results are equally discussed.
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2. Research Context

This work joins within the scope of a Big Data integration approach (Abbes & Gargouri, 2016a) such that the departure corpus is formed by Big Data, whereas the target schema is OWL (Ontology Web Language) (Owl, n.d.) ontology. The OWL language is chosen as the ontology representation language since it is the standard recommended by the World Wide Web Consortium (W3C) (W3C, n.d.) to represent ontologies. We are interested particularly to OWL-DL (Owl-dl, n.d.) since it supports the maximum expressiveness while retaining computational completeness and decidability.

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