The application of semi-supervised clustering in web services composition

Abstract

Semi-supervised classification algorithm using a large number of unlabeled data supporting the supervised learning process to improve the classification results. Web service composition is a complex interaction between the execution order to determine the different Web services and Web services. This article focuses on the semi-supervised clustering algorithm based on tags and constraints. The paper presents the application of Semi-supervised clustering in web services composition. The compared experimental results indicate that this method has great promise. © 2012 Springer-Verlag GmbH.