基于网络预测与用户偏好的服务推荐

With the increasing number of Web services on the Internet in recent years, the difficulty of service recommendation has gradually increased. This paper proposes a recommended method combining network prediction and collaborative filtering for the changes of services in the network over time and the history of service invocation of users. Firstly, the network model is constructed to transform the service prediction problem into network connection prediction. A rank aggregation algorithm is proposed to solve the connection prediction problem. Then the collaborative filtering algorithm is designed based on the user content and the call history. Finally, the experimental proof on the real data is proved. The effectiveness of this algorithm.