An Approach of Semantic Web Service Classification Based on Naive Bayes

Abstract

How to classify and organize the semantic Web services to help users find the services to meet their needs quickly and accurately is a key issue to be solved in the era of service-oriented software engineering. This paper makes full use the characteristics of solid mathematical foundation and stable classification efficiency of naive bayes classification method. It proposes a semantic Web service classification method based on the theory of naive bayes. It elaborates the concrete process of how to use the three stages of bayesian classification to classify the semantic Web services in the consideration of service interface and execution capacity. The information gain theory is used to determine the classification influence of different features. Finally, the experiments are used to validate the proposed methods.