Ontology Similarity Measure and Ontology Mapping Using Half Transductive Ranking

xiao huang, tianwei xu, wei gao, shu go

Abstract


Ontology similarity calculation and ontology mapping are important research topics in information retrieval. By analyzing the half transductive ranking algorithm, we propose the new algorithm for ontology similarity measure and ontology mapping. Via the ranking learning algorithm, the ontology graph is mapped into a line consists of real numbers. The similarity between two concepts then can be measured by comparing the difference between their corresponding real numbers. Experimental results show that the proposed algorithm has high accuracy and efficiency.

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