Goods Recommendation Fusing Credibility and Timeliness-tag

To solve improve the performance of e-commerce recommendation system, considering four graph model of credibility based on the user-projects-property-label of timeliness is proposed, And this paper proposes also a new recommendation algorithm-Goods Recommendation Fusing Credibility and Timeliness-tag(CRFCT) for the model.The model algorithm using reliability model judges user type to improve the cold start of the new project.3 kinds of personalized prediction scoring methods are proposed based on rating information and the attributes of the project and user timeliness method, incorporating the three evaluation methods, by adjusting the parameters of alpha, beta, and gamma balance factor to determine the weights of influence factors of the three evaluation methods, so as to improve the accuracy of recommendation.Experimenting show that has higher accuracy and also has higher novelty, and to some extent effective to deal with the cold start problem of the new project recommendation compared with the traditional recommendation algorithm.