An ontology mapping method based on support vector machine
Jie Liu, Linlin Qin, Hanshi Wang · 2013
Abstract. Ontology mapping has been applied widely in the field of semantic web. In this paper a new algorithm of ontology mapping were achieved. First, the new algorithms of calculating four individual similarities (concept name, property, instance and structure) between two concepts were mentioned. Secondly, the similarity vectors consisting of four weighted individual similarities were built, and the weights are the linear function of harmony and reliability, and the linear function can measure the importance of individual similarities. Here, each of ontology concept pairs was represented by a similarity vector. Lastly, Support Vector Machine (SVM) was used to accomplish mapping discovery by training the similarity vectors. Experimental results showed that, in our method, precision, recall and f-measure of ontology mapping discovery reached 95%, 93.5 % and 94.24%, respectively. Our method outperformed other existing methods. Introduction: In this paper, our study mainly is to discover the mapping [1] between concepts belonging to the different ontologies respectively. The proposed algorithm