中文版 | English

在结果中检索

CSpace

浏览/检索结果: 共6条，第1-6条 帮助

限定条件    
已选(0)清除 条数/页：   排序方式：
Non-Negative Latent Factor Model Based on beta-Divergence for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 8, 页码: 4612-4623
作者:  Xin, Luo;  Yuan, Ye;  Zhou, MengChu;  Liu, Zhigang;  Shang, Mingsheng
收藏  |  浏览/下载：130/0  |  提交时间：2021/08/20
beta-divergence  big data  high-dimensional and sparse (HiDS) matrix  industrial application  learning algorithm  non-negative latent factor (NLF) analysis  recommender system  
Reliability-Aware and Deadline-Constrained Mobile Service Composition Over Opportunistic Networks 期刊论文
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2021, 卷号: 18, 期号: 3, 页码: 1012-1025
作者:  Peng, Qinglan;  Xia, Yunni;  Zhou, MengChu;  Luo, Xin;  Wang, Shu;  Wang, Yuandou;  Wu, Chunrong;  Pang, Shanchen;  Lin, Mingwei
收藏  |  浏览/下载：174/0  |  提交时间：2021/08/20
Reliability  Mobile handsets  Mobile applications  Device-to-device communication  Cloud computing  Service computing  Quality of service  Intelligent optimization  Krill-Herd algorithm  mobile computing  mobile opportunistic network  mobile service composition  service reliability  
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：204/0  |  提交时间：2021/08/20
Big data  deep model  high-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  recommender system (RS)  
Latent Factor-Based Recommenders Relying on Extended Stochastic Gradient Descent Algorithms 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 2, 页码: 916-926
作者:  Luo, Xin;  Wang, Dexian;  Zhou, MengChu;  Yuan, Huaqiang
收藏  |  浏览/下载：67/0  |  提交时间：2021/03/17
Big data  bi-linear  collaborative filtering (CF)  high-dimensional and sparse (HiDS) matrix  industry  latent factor (LF) analysis  missing data  recommender system  
Non-Negativity Constrained Missing Data Estimation for High-Dimensional and Sparse Matrices from Industrial Applications 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 5, 页码: 1844-1855
作者:  Luo, Xin;  Zhou, MengChu;  Li, Shuai;  Hu, Lun;  Shang, Mingsheng
收藏  |  浏览/下载：124/0  |  提交时间：2020/08/24
Computational modeling  Data models  Sparse matrices  Linear programming  Training  Convergence  Analytical models  Alternating-direction-method of multipliers  high-dimensional and sparse matrix  industrial application  non-negative latent factor analysis  recommender system  
Temporal Pattern-Aware QoS Prediction via Biased Non-Negative Latent Factorization of Tensors 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 5, 页码: 1798-1809
作者:  Luo, Xin;  Wu, Hao;  Yuan, Huaqiang;  Zhou, MengChu
收藏  |  浏览/下载：372/0  |  提交时间：2020/08/24
Quality of service  Hidden Markov models  Data models  Training  Web services  Time factors  Latent factor analysis (LFA)  latent factorization of tensor  learning temporal pattern  linear bias (LB)  non-negative latent factorization of tensor  non-negativity constraint  quality-of-service (QoS) prediction