Classification of Web Services Using Tensor Space Model and Rough Ensemble Classifier

Abstract

The transition of the World Wide Web from a paradigm of static Web pages to one of dynamic Web services raises a new and challenging problem of locating desired web services. With the expected growth of the number of Web services available on the web, the need for mechanisms that enable the automatic categorization to organize this vast amount of data, becomes important. In this paper we propose Tensor space model for data representation and Rough Set based approach for the classification of Web services. The proposed tensor space model captures the information from internal structure of WSDL documents along with the corresponding text content. Rough sets are used here to combine information of the individual tensor components for providing classification results. Two step improvement on the existing classification results of web services has been shown here. In the first step we achieve better classification results over existing, by using proposed tensor space model. In the second step further improvement of the results has been obtained by using Rough set based ensemble classifier.