Metaheuristics-based ontology meta-matching approaches

•A systematic mapping on metaheuristics-based ontology meta-matching approaches.•An analysis of algorithms usually used in unsupervised and supervised approaches.•Answering research questions to guide new researchers in ontology meta-matching. Ontologies have emerged to establish a well-defined mean...

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Bibliographic Details
Published in:Expert systems with applications 2021-07, Vol.173, p.114578, Article 114578
Main Authors: Ferranti, Nicolas, Rosário Furtado Soares, Stênio Sã, de Souza, Jairo Francisco
Format: Article
Language:English
Subjects:
Data exchange
Evolutionary ontology matching
Heterogeneity
Knowledge representation
Matching
Metaheuristic-based ontology matching
Ontology
Ontology meta-matching
Problem solving
Semantics
Systematic mapping
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Summary:•A systematic mapping on metaheuristics-based ontology meta-matching approaches.•An analysis of algorithms usually used in unsupervised and supervised approaches.•Answering research questions to guide new researchers in ontology meta-matching. Ontologies have emerged to establish a well-defined meaning for information, solving problems of heterogeneity in data semantics and facilitating the process of information exchange. However, ontologies have generated a new semantic problem, since using more than one ontology can generate ambiguity in the meaning of a given data. The problem of ontology matching is to search for relationships between entities of distinct ontologies, solving the problem of semantic heterogeneity of the data. The problem is a relevant issue in the area of knowledge representation and several approaches have been proposed to solve it. This work presents a systematic mapping of the main works published in the area with an emphasis on metaheuristics-based meta-matching approaches.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2021.114578