A Logistic Factorization Model for Recommender Systems With Multinomial Responses
A Logistic Factorization Model for Recommender Systems With Multinomial Responses
复制标题
具有多项响应的推荐系统的逻辑分解模型
DOI：
10.1080/10618600.2019.1665535
复制
发表时间：
2020
影响因子：
2.4
通讯作者：
Qu, Annie
中科院分区：
文献类型：
--
作者：
Wang, Yu;Bi, Xuan;Qu, Annie
In this article, we propose a two-way multinomial logistic model for recommender systems for categorical ratings. Specifically, we treat the possible ratings as mutually exclusive events, whose probability is determined by the latent factor of the users and the items through a two-way multinomial logistic function. The proposed method has a compatibility with categorical ratings and the advantage of incorporating both the covariate information and the latent factors of the users and items uniformly. We show numerically that the proposed method performs consistently better than five commonly used collaborative filtering methods, namely, the restricted singular value decomposition, the soft-impute matrix completion method, the regression-based latent factor models, the restricted Boltzmann machine, and the group-specific recommender system on various simulation setups and on MovieLens data. Supplementary materials for this article are available online.
影响因子：
1.8
作者：
Sumit Ghosh;M. Mundhe;Karina Hernandez;S. Sen
通讯作者：
S. Sen