A review of semantic similarity approach for multiple ontologies

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 method...

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Main Authors: Omar, Nurul Aswa, Kasim, Shahreen, Md Fudzee, Mohd Farhan
Format: Article
Language:en
Published: Inderscience Enterprises Ltd. 2018
Subjects:
Online Access:http://eprints.uthm.edu.my/5549/1/AJ%202018%20%28576%29.pdf
http://eprints.uthm.edu.my/5549/
http://dx.doi.org/10.1504/IJIDS.2018.093921
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author Omar, Nurul Aswa
Kasim, Shahreen
Md Fudzee, Mohd Farhan
author_facet Omar, Nurul Aswa
Kasim, Shahreen
Md Fudzee, Mohd Farhan
author_sort Omar, Nurul Aswa
building UTHM Library
collection Institutional Repository
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
continent Asia
country Malaysia
description 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
format Article
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institution Universiti Tun Hussein Onn Malaysia
language en
publishDate 2018
publisher Inderscience Enterprises Ltd.
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spelling my.uthm.eprints-55492022-01-13T08:04:29Z http://eprints.uthm.edu.my/5549/ A review of semantic similarity approach for multiple ontologies Omar, Nurul Aswa Kasim, Shahreen Md Fudzee, Mohd Farhan QA71-90 Instruments and machines 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 Inderscience Enterprises Ltd. 2018 Article PeerReviewed text en http://eprints.uthm.edu.my/5549/1/AJ%202018%20%28576%29.pdf Omar, Nurul Aswa and Kasim, Shahreen and Md Fudzee, Mohd Farhan (2018) A review of semantic similarity approach for multiple ontologies. Int. J. Information and Decision Sciences, 10 (3). pp. 212-221. ISSN 1756-7017 http://dx.doi.org/10.1504/IJIDS.2018.093921
spellingShingle QA71-90 Instruments and machines
Omar, Nurul Aswa
Kasim, Shahreen
Md Fudzee, Mohd Farhan
A review of semantic similarity approach for multiple ontologies
title A review of semantic similarity approach for multiple ontologies
title_full A review of semantic similarity approach for multiple ontologies
title_fullStr A review of semantic similarity approach for multiple ontologies
title_full_unstemmed A review of semantic similarity approach for multiple ontologies
title_short A review of semantic similarity approach for multiple ontologies
title_sort review of semantic similarity approach for multiple ontologies
topic QA71-90 Instruments and machines
url http://eprints.uthm.edu.my/5549/1/AJ%202018%20%28576%29.pdf
http://eprints.uthm.edu.my/5549/
http://dx.doi.org/10.1504/IJIDS.2018.093921
url_provider http://eprints.uthm.edu.my/