Abstract To solve the sparseness problem of direct trust relationships in social networks and reduce the recommendation cost of traditional collaborative filtering algorithms, a three-way recommendation algorithm based on trust transfer mechanism is proposed. Firstly, a trust transfer mechanism is built to obtain the user's indirect trust relationships to expand the user's social networks. Secondly, the bipartite graph network structure is applied to calculate the bidirectional influence factors between users. Then, the bidirectional influence factors are regarded as the constraint term to design a new objective function to participate in the matrix factorization. Finally, the misclassification cost and promotion cost are taken into account in the recommendation process by introducing three-way decision, and thus a three-way recommendation algorithm based on objective function is presented. Experimental results on Filmtrust and Epinions datasets indicate that the proposed algorithm is superior to the traditional collaborative filtering algorithms.
Fund:Supported by National Natural Science Foundation of China(No.61902328), Applied Basic Research Programs of Science and Technology Department of Sichuan Province (2019YJ0314), Scientific Innovation Group for Youths of Sichuan Province (2019JDTD0017), College Students Innovation and Entrepreneurship Training Program of Sichuan Province (S20190615090), Southwest Petroleum University Undergraduate Teaching Reform Research Project (X2018KZ077)
Corresponding Authors:
ZHANG Hengru, Ph.D., professor. His research interests include recommender system, granular computing and artificial intelligence security.
About author:: QIN Qin, master student. Her research interests include recommender system.
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2020, Vol. 33 
