From Ontology to Semantic Similarity: Calculation of Ontology-Based Semantic Similarity
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. Ontologi...
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2013/793091 |
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| _version_ | 1832552103757742080 |
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| author | Mingxin Gan Xue Dou Rui Jiang |
| author_facet | Mingxin Gan Xue Dou Rui Jiang |
| author_sort | Mingxin Gan |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-ecbf21c603fc4cdba43a213da3b6594d |
| institution | Kabale University |
| issn | 1537-744X |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-ecbf21c603fc4cdba43a213da3b6594d2025-02-03T05:59:37ZengWileyThe Scientific World Journal1537-744X2013-01-01201310.1155/2013/793091793091From Ontology to Semantic Similarity: Calculation of Ontology-Based Semantic SimilarityMingxin Gan0Xue Dou1Rui Jiang2Dongling School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, ChinaDongling School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, ChinaDepartment of Automation, Tsinghua University, Beijing 100084, ChinaAdvances 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.http://dx.doi.org/10.1155/2013/793091 |
| spellingShingle | Mingxin Gan Xue Dou Rui Jiang From Ontology to Semantic Similarity: Calculation of Ontology-Based Semantic Similarity The Scientific World Journal |
| title | From Ontology to Semantic Similarity: Calculation of Ontology-Based Semantic Similarity |
| title_full | From Ontology to Semantic Similarity: Calculation of Ontology-Based Semantic Similarity |
| title_fullStr | From Ontology to Semantic Similarity: Calculation of Ontology-Based Semantic Similarity |
| title_full_unstemmed | From Ontology to Semantic Similarity: Calculation of Ontology-Based Semantic Similarity |
| title_short | From Ontology to Semantic Similarity: Calculation of Ontology-Based Semantic Similarity |
| title_sort | from ontology to semantic similarity calculation of ontology based semantic similarity |
| url | http://dx.doi.org/10.1155/2013/793091 |
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