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An Inherently Nonnegative Latent Factor Model for High-Dimensional and Sparse Matrices from Industrial Applications 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 卷号: 14, 期号: 5, 页码: 2011-2022
作者:  Luo, Xin;  Zhou, MengChu;  Li, Shuai;  Shang, MingSheng
收藏  |  浏览/下载:508/0  |  提交时间:2018/07/02
Big data  high-dimensional and sparse matrix  learning algorithms  missing-data estimation  nonnegative latent factor analysis  optimization methods recommender system  
A Novel Approach to Extracting Non-Negative Latent Factors From Non-Negative Big Sparse Matrices 期刊论文
IEEE ACCESS, 2016, 卷号: 4, 页码: 2649-2655
作者:  Luo, Xin;  Zhou, Mengchu;  Shang, Mingsheng;  Li, Shuai;  Xia, Yunni
Adobe PDF(9487Kb)  |  收藏  |  浏览/下载:878/1  |  提交时间:2018/03/15
Latent factors  non-negativity  matrix factorization  non-negative big sparse matrix  big data  recommender system  
Symmetric and Nonnegative Latent Factor Models for Undirected, High-Dimensional, and Sparse Networks in Industrial Applications 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2017, 卷号: 13, 期号: 6, 页码: 3098-3107
作者:  Luo, Xin;  Sun, Jianpei;  Wang, Zidong;  Li, Shuai;  Shang, Mingsheng
Adobe PDF(803Kb)  |  收藏  |  浏览/下载:427/0  |  提交时间:2018/03/05
Big data application  high-dimensional, and sparse (SHiDS) matrix  nonnegative latent factor (NLF) model  symmetry  undirected HiDS network  
Long-term performance of collaborative filtering based recommenders in temporally evolving systems 期刊论文
NEUROCOMPUTING, 2017, 卷号: 267, 页码: 635-643
作者:  Shi, Xiaoyu;  Luo, Xin;  Shang, Mingsheng;  Gu, Liang
收藏  |  浏览/下载:108/0  |  提交时间:2018/03/05
Learning system  Recommender system  One-step recommendation  Long-term effect  Temporally evolving system  Bipartite network  
Incremental Slope-one recommenders 期刊论文
NEUROCOMPUTING, 2018, 卷号: 272, 页码: 606-618
作者:  Wang, Qing-Xian;  Luo, Xin;  Li, Yan;  Shi, Xiao-Yu;  Gu, Liang;  Shang, Ming-Sheng
收藏  |  浏览/下载:159/0  |  提交时间:2018/03/05
Collaborative Filtering  Slope-one  Recommender System  Dynamic Datasets  Incremental Recommenders