EconPapers    
Economics at your fingertips  
 

A review of semantic similarity approach for multiple ontologies

Nurul Aswa Omar, Shahreen Kasim and Mohd Farhan Md Fudzee

International Journal of Information and Decision Sciences, 2018, vol. 10, issue 3, 212-221

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. (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=93921 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijidsc:v:10:y:2018:i:3:p:212-221

Access Statistics for this article

More articles in International Journal of Information and Decision Sciences from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().

 
Page updated 2025-03-19
Handle: RePEc:ids:ijidsc:v:10:y:2018:i:3:p:212-221