Hybrid collaborative filtering model for consumer dynamic service recommendation based on mobile cloud information system

Abstract

The rapid development of the web has led to a considerable increase in information dissemination. Recently, personalized web service recommendation has become a popular research area in service computing. Research on web service recommendation systems mainly addresses two problems: prediction and completion of sparse QoS data, and the user's personalized recommendation. To address the issue of high data sparsity and low recommendation accuracy in the traditional service recommendation models under mobile cloud, this study presents a hybrid collaborative filtering model for consumer service recommendation based on mobile cloud by introducing user preferences. The example verified that the service recommendation based on the model can effectively reduce the data sparsity and increase the accuracy of the prediction.