基于支持向量机的中文模糊本体映射

Chinese Fuzzy Ontology Mapping Based on Support Vector Machine

Taking into account that fuzzy ontology mapping has wide application and cannot be dealt with in many fields at present, a Chinese fuzzy ontology model and a method for Chinese fuzzy ontology mapping are proposed. The mapping discovery between two ontologies is achieved by computing the similarity between the concepts of two ontologies. Every concept consists of four features of concept name, property, instance and structure. First, the algorithms of calculating four individual similarities corresponding to the four features are given. Secondly, the similarity vectors consisting of four weighted individual similarities are built, and the weights are the linear function of harmony and reliability. The similarity vector is used to represent the similarity relation between two concepts which belong to different fuzzy ontolgoies. Lastly, Support Vector Machine (SVM) is used to get the mapping concept pairs by the similarity vectors. Experiment results are satisfactory.