Time-aware Service Recommendation Based on Dynamic Preference and QoS

The historical data of services usage shows us that both user preference and service quality are dynamic, and service quality has a certain influence on user preference. Due to the dynamic characteristics of both user preference and quality of service (QoS), how to recommend the best suitable services to users has become an urgent problem to be solved. But the most service recommendation approaches neglect the cyclical feature in dynamic preference model, and also neglect the impact of QoS on the user preference. We propose a time-aware recommendation method which considers the dynamic preference, the dynamic QoS and the impact of QoS on user preference comprehensively. Our experiments conducted on the real-world dataset WS-Dream, and the results show that our proposed approach outperforms several classical approaches and state-of-the-art approaches in terms of accuracy, recall, F1-value and Hamming distance.