Collaborative Filtering Based Hybrid Approach for Web Service Recommendations

摘要

Now a days, Web services are becoming the primary source for constructing software system over Internet. The quality of whole system greatly dependents on the QoS of single web service, so QoS information is an important indicator for service selection. But in reality, QoSs of some Web Services may be unavailable for users. How to predicate the missing QoS value of Web service through fully using the existing information is a difficult problem. This study first proposes a novel method for clustering similar web services using semantic approach in order to overcome the limitations of pattern-matching approach and finally proposes a cluster based approach using Slope One Collaborative filtering method to predict the QoS values for similar web services for similar users. Proposed approaches are applied on a dataset consisting of WSDL files and QoS values for various QoS parameters which are collected from the Internet and the proposed approaches shows better qualities with respect to clusters formed and the QoS values predicted.