Unifying ontological similarity measures: A theoretical and empirical investigation
| Autor: | Xinran Yu, Xueheng Hu, Valerie Cross |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Information retrieval
Basis (linear algebra) business.industry Gene ontology Applied Mathematics Mouse Anatomy Parameterized complexity computer.software_genre Theoretical Computer Science Semantic similarity Artificial Intelligence Similarity (psychology) Artificial intelligence business Wu's method of characteristic set computer Software Natural language processing Mathematics |
| Zdroj: | International Journal of Approximate Reasoning. 54:861-875 |
| ISSN: | 0888-613X |
| DOI: | 10.1016/j.ijar.2013.03.003 |
| Popis: | This paper theoretically and empirically investigates ontological similarity. Tversky’s parameterized ratio model of similarity [3] is shown as a unifying basis for many of the well-known ontological similarity measures. A new family of ontological similarity measures is proposed that allows parameterizing the characteristic set used to represent an ontological concept. The three subontologies of the prominent Gene Ontology (GO) are used in an empirical investigation of several ontological similarity measures. Another study using well known semantic similarity within two different anatomy ontologies, the NCIT anatomy and the mouse anatomy, is also presented for comparison to several of the GO results. A discussion of the correlation among the measures is presented as well as a comparison of the effects of two different methods of determining a concept’s information content, corpus-based and ontology-based. |
| Databáze: | OpenAIRE |
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