关键词: Web服务, 服务质量预测, 协同过滤, SlopeOne, 分类与回归树

Abstract: Aiming at the problem that the existing Web service QoS prediction approaches did not take the characteristics of users-service into consideration,a prediction algorithm based on Classification and Regression Trees (CART) and SlopeOne was proposed.The history QoS value was first employed to extract the users and services features and then classify user-service pair with CART based on the extracted features.To improve the prediction accuracy,SlopeOne was used to predict QoS on the target user and the target service's classification result.The experiments on a real-world dataset were conducted,and the experimental results illustrated that the proposed method had better prediction accuracy than baseline models.

Key words: Web service, QoS prediction, collaborative filtering, SlopeOne, classification and regression tree