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An L-1-and-L-2-Norm-Oriented Latent Factor Model for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 14
作者:  Wu, Di;  Shang, Mingsheng;  Luo, Xin;  Wang, Zidong
收藏  |  浏览/下载:42/0  |  提交时间:2022/08/22
High-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  L-1 norm  L-2 norm  recommender system (RS)  
An alpha -beta -Divergence-Generalized Recommender for Highly Accurate Predictions of Missing User Preferences 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2021, 页码: 13
作者:  Shang, Mingsheng;  Yuan, Ye;  Luo, Xin;  Zhou, MengChu
收藏  |  浏览/下载:53/0  |  提交时间:2022/08/22
Computational modeling  Sparse matrices  Convergence  Data models  Predictive models  Linear programming  Euclidean distance  -divergence  big data  convergence analysis  high-dimensional and sparse (HiDS) data  momentum  machine learning  missing data estimation  non-negative latent factor analysis (NLFA)  recommender system (RS)  
Highly-Accurate Community Detection via Pointwise Mutual Information-Incorporated Symmetric Non-Negative Matrix Factorization 期刊论文
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2021, 卷号: 8, 期号: 1, 页码: 463-476
作者:  Luo, Xin;  Liu, Zhigang;  Shang, Mingsheng;  Lou, Jungang;  Zhou, MengChu
收藏  |  浏览/下载:145/0  |  提交时间:2021/04/20
Detectors  Symmetric matrices  Image edge detection  Social networking (online)  Topology  Measurement  Knowledge engineering  Computational Intelligence  Social Network  Network Representation  Community Detection  Pointwise Mutual Information  Symmetric and Non-negative Matrix Factorization  Graph-regularization