关键词: Web服务, 服务质量预测, 协同过滤, 客户端上下文

Abstract:

Since the Web services with similar functions are published into Internet, quality of service (QoS) has played an important role in services selection. The identifying client context features between different users is helpful to predict QoS accurately. However, these context features affecting the experience quality of user have not been analyzed systematically in current studies. A client context-aware prediction approach of QoS for Web services was proposed, in which the client context features, including geographical location, network location, and device were analyzed quantitatively. The fuzzy analytic hierarchy process method was applied to calculate context similarity between current user and history users. From that, the similarity weights fusion method was employed to predict the QoS, integrating the collaborative filtering technology. Experiment analysis indicates that this approach can solve the new user problem and improve the accuracy of QoS prediction of Web services effectively.

Key words: Web services, quality of service prediction, collaborative filtering, client context