Abstract: Recommender system has achieved great success in dealing with information overload,meanwhile has some problems,such as data sparse,cold start and so on.How to get satisfied recommendation under the circumstance of data sparse is urgent for recommender system.Introducing trust into recommender system is an efficient way to resolve the above problems.Most of existing trust-aware recommender systems are based on Boolean trust relationship,and do not take domain correlation of trust into account.In the field of service selection,service requestor selects services based on QoS(quality of service).Inspired by QoS,recommendation requestor can find recommender based on QoR(quality of recommendation).Thus we put forward the concept of QoR and QoR based trust-aware recommender system．The attributes of qor include user rating similarity,domain trust,domain relative degree and social intimacy degree,whose weights are determined by method of information entropy.Empirical evaluation shows that our method improves the precision and ra-ting coverage of recommender system under condition of data sparse,above all,effectively improves the recall rate of cold start user,resolving the cold start problem to some extend.

Key words: Service recommendation,Quality of recommendation,Trust