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A Multilayered-and-Randomized Latent Factor Model for High-Dimensional and Sparse Matrices 期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2022, 卷号: 8, 期号: 3, 页码: 784-794
作者:  Yuan, Ye;  He, Qiang;  Luo, Xin;  Shang, Mingsheng
收藏  |  浏览/下载：75/0  |  提交时间：2022/08/22
Computational modeling  Sparse matrices  Big Data  Data models  Stochastic processes  Training  Software algorithms  Big data  latent factor analysis  generally multilayered structure  deep forest  multilayered extreme learning machine  randomized-learning  high-dimensional and sparse matrix  stochastic gradient descent  randomized model  
Large-Scale and Scalable Latent Factor Analysis via Distributed Alternative Stochastic Gradient Descent for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2022, 卷号: 8, 期号: 2, 页码: 420-431
作者:  Shi, Xiaoyu;  He, Qiang;  Luo, Xin;  Bai, Yanan;  Shang, Mingsheng
收藏  |  浏览/下载：71/0  |  提交时间：2022/08/22
Recommender systems  Training  Optimization  Big Data  Cloud computing  Computational modeling  Sparse matrices  Recommender system  latent factor analysis  high-dimensional and sparse matrices  alternative stochastic gradient descent  distributed computing  
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：146/0  |  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  
Symmetric Nonnegative Matrix Factorization-Based Community Detection Models and Their Convergence Analysis 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13
作者:  Luo, Xin;  Liu, Zhigang;  Jin, Long;  Zhou, Yue;  Zhou, MengChu
收藏  |  浏览/下载：54/0  |  提交时间：2022/08/22
Detectors  Convergence  Symmetric matrices  Social networking (online)  Analytical models  Tuning  Computational modeling  Community detection  convergence analysis  graph regularization  nonnegative multiplicative update (NMU)  social network analysis  symmetric and nonnegative matrix factorization (SNMF)  
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  
Identifying the influential nodes via eigen-centrality from the differences and similarities of structure 期刊论文
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2018, 卷号: 510, 页码: 77-82
作者:  Zhong, Lin-Feng;  Shang, Ming-Sheng;  Chen, Xiao-Long;  Cai, Shi-Ming
Adobe PDF(433Kb)  |  收藏  |  浏览/下载：124/0  |  提交时间：2018/11/01
Complex Network  Influential Node  Eigen-centrality  Sir  Kendall  
Emerging trends in evolving networks: Recent behaviour dominant and non-dominant model 期刊论文
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2017, 卷号: 484, 页码: 506-515
作者:  Abbas, Khushnood;  Shang, Mingsheng;  Luo, Xin;  Abbasi, Alireza
Adobe PDF(2072Kb)  |  收藏  |  浏览/下载：101/0  |  提交时间：2018/03/05
Novelty  Evolving networks  Recommender systems  E-commerce  Collective behaviour  Trend prediction  Emerging behaviour  
Coarse cluster enhancing collaborative recommendation for social network systems 期刊论文
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2017, 卷号: 483, 页码: 209-218
作者:  Zhao, Yao-Dong;  Cai, Shi-Min;  Tang, Ming;  Shang, Min-Sheng
Adobe PDF(909Kb)  |  收藏  |  浏览/下载：101/0  |  提交时间：2018/03/05
Recommender system  Social network system  Social tagging system  Tripartite graph  Time complexity  Collaborative user model  
User Heterogeneity and Individualized Recommender 期刊论文
CHINESE PHYSICS LETTERS, 2017, 卷号: 34, 期号: 6, 页码: 4
作者:  Wang, Qing-Xian;  Zhang, Jun-Jie;  Shi, Xiao-Yu;  Shang, Ming-Sheng
Adobe PDF(566Kb)  |  收藏  |  浏览/下载：80/0  |  提交时间：2018/03/05