Research On Semantic Web Service Matching Algorithm Based On Similarity Of Ontology

Be confronted with so many Web services, it is necessary to solve the problem of how to find required services quickly and effectively in service matching field. The precision and accuracy of UDDI query method based on keywords are not satisfactory. The emergence of Semantic Web technology provides the semantic support for service matching and service discovery.Currently, the semantic Web services matching mainly are achieved by measuring similarity based on service description in ontology. Therefore, service matching is also considered the similarity calculations based on the concept of ontology. For the different relationships between concepts in Ontology structures, through researching on corresponding algorithms of semantic similarity, this paper mainly completes the work in three aspects:1.considering the IS-A relationship exists only in ontology, a simple and effective hybrid algorithm of computing semantic similarity between the concepts is proposed.For the feature in IS-A relationship between the concepts, analyzes the semantic similarity computing method of Network model and information theory, proposes a hybrid algorithm. This method computes the concept information content by information theory firstly, and then adjusts the weights of edges through the hierarchy of concept information, finally, computes the shortest semantic distance between concepts by using the network distance model method, to attain the semantic similarity between them.This method not only considers the effect of similarity that relate to depth and density,but also limits the computing of concept information content and edges weight into a sub-tree generated in ontology, which reduces the computational complexity.2.The two layers semantic matching model is constructed to improve the efficiency of the service matching.Combining the Semantic reasoning and hybrid method proposed by this paper, to construct two layers semantic matching model, which is using OWL describing logic for semantic reasoning firstly, to reduce the scale of the issue, and then computes the semantic distance.3.Considers the other relationship and similar asymmetry between concepts, proposes a matching method of concept similarity based on fuzzy set. The main idea of this method is to describe the concept feature using set of semantic features of the concept, and the similarity measurement for concepts can be transformed into computing of similarity in fuzzy feature set. In this method, according to IS-A relationship, attribute relationship between concepts and the feature of asymmetric semantic similarity firstly, sets the corresponding weight, to attain the semantic relation matrix through corresponding matrix operations. Based on it, obtains the concept semantic feature set SFS and fuzzy feature FFS, finally, measure the semantic similarity between two concepts by calculating the similarity between two fuzzy sets to achieve the matching service. Finally, the feasibility and effectiveness of the method are verified by experiment.This method comprehensively considers that factors that influence the similarity of concepts compared with other method,it provides a better method for the calculation of similarity...