Extended TvX: A New Method Feature Based Semantic Similarity for Multiple Ontology

Authors

  • Nurul Aswa Omar Department Web Technology, Faculty Computer Sciences and Information Technology, Universiti Tun Hussein Onn Malaysia, Malaysia.
  • Shahreen Kasim Soft Computing And Data Mining Center, Faculty Computer Sciences and Information Technology, Universiti Tun Hussein Onn Malaysia, Malaysia.
  • Mohd Farhan Md Fudzee Department Multimedia, Faculty Computer Sciences and Information Technology, Universiti Tun Hussein Onn Malaysia, Malaysia.

Keywords:

Semantic Similarity, Feature Based, Ontology, Multiple Ontology, Cross Ontology, Heterogeneous Sources,

Abstract

Semantic similarity between the terms is the main phase in information retrieval and information integration, which requires semantic content matching. Semantic similarity function is important in psychology, artificial intelligence and cognitive science. The problem of integrating various sources is the matching between ontological concepts. In this paper, we proposed to develop this method by analyzing the semantic similarity between the modeled taxonomical knowledge and features in different ontology. This paper contains a review on semantic similarity and multiple ontology that focuses on the feature-based approach. Besides that, we proposed a method, namely a semantic similarity that overcomes the limitation of different features of terms compared. As a result, we are able to develop a better method that improves the accuracy of the similarity measurement.

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Published

2017-06-01

How to Cite

Omar, N. A., Kasim, S., & Md Fudzee, M. F. (2017). Extended TvX: A New Method Feature Based Semantic Similarity for Multiple Ontology. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2-3), 39–43. Retrieved from https://jtec.utem.edu.my/jtec/article/view/2270

Issue

Vol. 9 No. 2-3: Circuit and System Advancement in Modern World II

Section

Articles

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