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A Latent Factor Analysis-Based Approach to Online Sparse Streaming Feature Selection 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 页码: 15
作者:  Wu, Di;  He, Yi;  Luo, Xin;  Zhou, MengChu
收藏  |  浏览/下载:61/0  |  提交时间:2022/08/22
Big data  computational intelligence  latent factor analysis (LFA)  missing data  online algorithm  online feature selection  sparse streaming feature  streaming feature  
A Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 7, 页码: 4285-4296
作者:  Wu, Di;  Luo, Xin;  Shang, Mingsheng;  He, Yi;  Wang, Guoyin;  Zhou, MengChu
收藏  |  浏览/下载:238/0  |  提交时间:2021/08/20
Big data  deep model  high-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  recommender system (RS)  
Algorithms of Unconstrained Non-Negative Latent Factor Analysis for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2021, 卷号: 7, 期号: 1, 页码: 227-240
作者:  Luo, Xin;  Zhou, Mengchu;  Li, Shuai;  Wu, Di;  Liu, Zhigang;  Shang, Mingsheng
收藏  |  浏览/下载:163/0  |  提交时间:2021/05/17
Data models  Training  Sparse matrices  Recommender systems  Computational modeling  Big Data  Scalability  Non-negative latent factor analysis  non-negativity  latent factor analysis  unconstrained optimization  high-dimensional and sparse matrix  collaborative filtering  recommender system  big data