Personalized recommendation algorithm based on multi-perspective trust

doi:10.3969/j.issn.1000-1565.2020.05.014

Journal of Hebei University (Natural Science Edition) ›› 2020, Vol. 40 ›› Issue (5): 552-560.DOI: 10.3969/j.issn.1000-1565.2020.05.014

Personalized recommendation algorithm based on multi-perspective trust

REN Zhibo¹, WANG Yawen², WEI Xiangyu³, GUAN Chengkang⁴

1. Liberal Arts Comprehensive Experimental Center, Hebei University, Baoding 071002, China; 2. College of Management, Hebei University, Baoding 071002, China; 3. School of Humanities and Sciences, Northeast Petroleum University, Daqing 163318, China; 4. School of Information Science and Technology, Xiamen University Malaysia, Sepang 43900, Selangor Darul Ehsan, Malaysia

Received:2019-03-05 Online:2020-09-25 Published:2020-09-25

Abstract

Abstract: By giving the adaptive weight to the users trust in project score data and social trust, a comprehensive personalized recommendation algorithm combining multi-view trust and probability matrix decomposition was proposed to improve the recommendation accuracy. The algorithm was verified on the Filmtrust dataset. The results showed that the proposed algorithm was effectively improved on both MAE(mean absolute error)and RMSE(root mean squared error)indicators compared with related algorithms.

Key words: trust, probabilistic matrix factorization, collaborative filtering, personalized recommendation

CLC Number:

REN Zhibo, WANG Yawen, WEI Xiangyu, GUAN Chengkang. Personalized recommendation algorithm based on multi-perspective trust[J]. Journal of Hebei University (Natural Science Edition), 2020, 40(5): 552-560.

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Personalized recommendation algorithm based on multi-perspective trust

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