Abstract：The semantic similarity computing between concepts is an important component in natural language processing etc., and the semantic similarity computing between concepts based on semantic distance is currently dominant technique. In this paper, the ontology based cluster partition approach for computing the semantic distance between concepts is proposed on the basis of the analysis of the lacks in the existing algorithms. The rules for computing the semantic distance between concepts are given under the situation of multiconcept clusters, and then the approach for computing the semantic distance between concepts within single cluster as well as crosscluster is put forward. In the proposed approach, the nonsymmetry of semantic similarities in the pairs of hyponymy concepts is worked out by introducing the forward semantic distance and the reverse semantic distance, and the other binary relationships of the pairs of nonhyponymy concepts are deal with by dynamically allocating the relation weights in the light of the locations of concept nodes. Experimented results shows that the proposed approach is effective and it is preferable to other typical similar ones.
2011, Vol. 24 
