The Research For Semantic Web Service Index Based On User Preference

Now, with the development of the Internet, network technology become more and more advanced, network resources are also showing explosive growth, so the handling of the network resources is becoming increasingly difficult, because it is prone to the same or similar resources, and users really do not know how to choose and how to query, so the concept of the semantic Web has been proposed. At the same time, there are a large number of Web services in a network environment, and these Web services are widely used in industry and business community, these Web services due to the lack of semantic information, so users have to face a number of Web services with same function or similar function. To add semantic information to Web services, and make Web services become semantic Web services, this method can improve the accuracy of the service query, and can find more similar services which allows the user to have more choices.In the query process, due to the large number of semantic similarity calculation, the reaction is very slow to find a match for Semantic Web Services, seriously affecting the user experience. Therefore, in the process of semantic Web service matching, through research of the ontological characteristics and user preferences, this paper proposes an efficient query index of the Semantic Web Services, including ontology index based clustering and the optimization algorithm which can reduce the calculation of semantic similarity. Through simulation experiments, the method is proved to be feasible and reasonable, especially in a huge number of semantic Web Services or the concept of the ontology is huge. On the other hand, it can significantly reduce the calculation of semantic similarity, screening out some semantic Web Services related and unrelated to the user queries. Overall, our method can improve the reflect speed in search system, while improving the user experience.