Ontology similarity computation using k-partite ranking method
Wei Dong Gao · Journal of Computer Applications · 2012
This paper represented the information of each vertex in ontology graph as a vector.According to its structure of ontology graph,the vertices were divided into k parts.It chose vertices from each part,and chose the ranking loss function.It used k-partite ranking learning algorithm to get the optimization ranking function,mapped each vertex of ontology structure graph into a real number,and then calculated the relative similarities of concepts by comparing the difference between real numbers.The experimental results show that the method for calculating the relative similarity between the concepts of ontology is effective.