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The Scientific World Journal
Volume 2013, Article ID 793091, 11 pages
Review Article

From Ontology to Semantic Similarity: Calculation of Ontology-Based Semantic Similarity

1Dongling School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China
2Department of Automation, Tsinghua University, Beijing 100084, China

Received 27 October 2012; Accepted 16 January 2013

Academic Editors: Y. Cai, S. Mohan, C. Proctor, K. Spiegel, and J. Wang

Copyright © 2013 Mingxin Gan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Advances in high-throughput experimental techniques in the past decade have enabled the explosive increase of omics data, while effective organization, interpretation, and exchange of these data require standard and controlled vocabularies in the domain of biological and biomedical studies. Ontologies, as abstract description systems for domain-specific knowledge composition, hence receive more and more attention in computational biology and bioinformatics. Particularly, many applications relying on domain ontologies require quantitative measures of relationships between terms in the ontologies, making it indispensable to develop computational methods for the derivation of ontology-based semantic similarity between terms. Nevertheless, with a variety of methods available, how to choose a suitable method for a specific application becomes a problem. With this understanding, we review a majority of existing methods that rely on ontologies to calculate semantic similarity between terms. We classify existing methods into five categories: methods based on semantic distance, methods based on information content, methods based on properties of terms, methods based on ontology hierarchy, and hybrid methods. We summarize characteristics of each category, with emphasis on basic notions, advantages and disadvantages of these methods. Further, we extend our review to software tools implementing these methods and applications using these methods.