Title :
Ontology-based semantic similarity: A new approach based on analysis of the concept intent
Author :
Jian-Bo Gao ; Bao-Wen Zhang ; Xiao-Hua Chen
Author_Institution :
Inf. Security Dept., Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
Ontology offers a structured knowledge representation and provides formal interpretation of concepts which can be used in semantic similarity measuring. In this paper, we analyze these ontology-based approaches for semantic similarity computation and propose a new ontology-based measure relying on exploiting intent of the concept. Our measurement combines the idea of two popular semantic similarity calculation approaches: graph-based approaches and feature-based measures. In order to compute the semantic similarity of concepts in ontology, a new algorithm is presented. We compare results obtained by our method with other two typical approaches, the results show that our measurement can distinguish fine differences between concepts and thus has finer granularity.
Keywords :
graph theory; ontologies (artificial intelligence); concept intent; feature-based measures; graph-based approach; ontology-based measure; ontology-based semantic similarity; structured knowledge representation; Abstracts; Equations; Mathematical model; Semantics; Concept intent; Feature-based measure; Formal; Ontology; Semantic similarity;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2013 International Conference on
Conference_Location :
Tianjin
DOI :
10.1109/ICMLC.2013.6890375