Computing Concept Relatedness Based on Ontology
| Autor: | Xingwei Hao, Shaocun Tian, Yanping Lu |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Knowledge management
Computer science business.industry Ontology-based data integration InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL Suggested Upper Merged Ontology Ontology (information science) Similarity measure computer.software_genre Taxonomy (general) Similarity (psychology) Upper ontology Relevance (information retrieval) Artificial intelligence business computer Natural language processing |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783642549298 |
| Popis: | Concept relatedness is widely used in information retrieval, text classification, semantic extension, and other fields. So measuring the concept relatedness efficiently is an important task. Previous studies rarely distinguish between relatedness and similarity; they usually use a common formula. We suggest that concept relatedness consists of similarity and relevance, which should be computed differently. In this paper, we first give a similarity measure based on path length, taxonomy depth, and different relations between concepts. Then we propose a method to measure the specific association relation besides basic relations. Finally, incorporating both similarity and specific relevance, we get an overall formula of computing concept relatedness. Compared to existing methods, our measure of concept relatedness is more consistent with human judgment. |
| Databáze: | OpenAIRE |
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