An improved collaborative filtering recommendation algorithm based on factor of credit

Traditional collaborative filtering algorithm is a weighted average prediction algorithm based on nearest neighbors' ratings. Besides similarity between users, trust and credit are also parameters to affect recommendation. This paper proposes a computational model of credit factor and then a collaborative filtering algorithm based on it. This model is based on trust factor and takes credit model as the basic elements. This proposed algorithm further improves the validity and accuracy of the recommendation.