Collaborative recommendation method improvement based on social network analysis
Xiaowan DANG · Journal of Computer Applications · 2013
Collaborative recommendation is widely used in E-commerce personalized service.But the existing methods cannot provide high level personalized service due to sparse data and cold start.To improve the accuracy of collaborative recommendation,a collaborative recommendation method based on Social Network Analysis(SNA) was proposed in this paper by using SNA to improve the collaborative recommendation methods.The proposed method used SNA technology to analyze the trust relationships between users,then quantified the relationships as trust values to fill the user-item matrix,and used these trust values to calculate the similarity of users.The effectiveness of the proposed method was verified by the experimental analysis.Using trust values to expand the user-item matrix can not only solve the problem of sparse data and cold start effectively,but also improve the accuracy of collaborative recommendation.