Title: A review of semantic similarity approach for multiple ontologies

Authors: Nurul Aswa Omar; Shahreen Kasim; Mohd Farhan Md Fudzee

Addresses: Department Web Technology, Faculty Computer Sciences and Information Technology, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Johor, Malaysia ' Software Multimedia Center, Faculty Computer Sciences and Information Technology, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Johor, Malaysia ' Department Multimedia, Faculty Computer Sciences and Information Technology, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Johor, Malaysia

Abstract: Measuring semantic similarity between concepts is an important step in information retrieval and information integration which requires semantic content matching. Semantic similarity has attracted great concern for a long time in artificial intelligence, psychology and cognitive science. Many methods have been proposed. This paper contains a review on the state of art approaches including structure-based approach, information content-based approach, feature-based approach and hybrid-based approach. We also discussed the similarity according to their advantages, disadvantages and issues related to multiple ontologies. Besides that, we also concentrated on methods in feature-based approach which we will be using as a mechanism to measure the similarity for multiple ontologies.

Keywords: semantic similarity; feature-based; ontology; multiple ontology; cross ontology; heterogeneous sources.

DOI: 10.1504/IJIDS.2018.093921

International Journal of Information and Decision Sciences, 2018 Vol.10 No.3, pp.212 - 221

Received: 03 Jul 2015
Accepted: 25 Aug 2016
Published online: 09 Aug 2018 *

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