By giving the adaptive weight to the users 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.
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
.
DOI: 10.3969/j.issn.1000-1565.2020.05.014
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