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Association Rule Ontology Matching Approach

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  • Jérôme David

    (Polytechnic School of Nantes University, France)

Abstract

This article presents a hybrid, extensional and asymmetric matching approach designed to find out relations (equivalence and subsumption) between two textual hierarchies. By using the as-sociation rule paradigm and a statistical measure, this method relies on the following idea: ``An entity A will be more specific than or equivalent to an entity B if the vocabulary used to describe A and its instances tends to be included in that of B and its instances’’. This approach is divided into two parts: (1) The representation of each entity by a set of relevant terms and data; (2) The discovery of binary association rules between entities. The selection of rules uses two criteria for assessing the implication quality and reducing redundancy. The method is evaluated on two benchmarks. The first contains two hierarchies indexing textual documents and the second one is composed of OWL ontologies.

Suggested Citation

  • Jérôme David, 2007. "Association Rule Ontology Matching Approach," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 3(2), pages 27-49, April.
    • Handle: RePEc:igg:jswis0:v:3:y:2007:i:2:p:27-49
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    Cited by:

    1. Hai Zhu & Xingsi Xue & Hongfeng Wang, 2022. "Matching Ontologies through Multi-Objective Evolutionary Algorithm with Relevance Matrix," Mathematics, MDPI, vol. 10(12), pages 1-12, June.
    2. Ahmad Zaeri & Mohammad Nematbakhsh, 2012. "A Terminological Search Algorithm for Ontology Matching," Modern Applied Science, Canadian Center of Science and Education, vol. 6(10), pages 1-37, October.

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