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A momentum-incorporated latent factorization of tensors model for temporal-aware QoS missing data prediction 期刊论文
NEUROCOMPUTING, 2019, 卷号: 367, 页码: 299-307
作者:  Wang, Qingxian;  Chen, Minzhi;  Shang, Mingsheng;  Luo, Xin
收藏  |  浏览/下载:445/0  |  提交时间:2019/12/03
Big Data  QoS prediction  Temporal-aware QoS prediction  Stochastic gradient descent  Latent factorization of tensors  Momentum method  
Elastic-net regularized latent factor analysis-based models for recommender systems 期刊论文
NEUROCOMPUTING, 2019, 卷号: 329, 页码: 66-74
作者:  Wang, Dexian;  Chen, Yanbin;  Guo, Junxiao;  Shi, Xiaoyu;  He, Chunlin;  Luo, Xin;  Yuan, Huaqiang
Adobe PDF(1965Kb)  |  收藏  |  浏览/下载:213/0  |  提交时间:2019/01/17
Big data  Recommender systems  Collaborative filtering  Latent factor analysis  Elastic-net  Regularization  Latent factor distribution  
An adaptive latent factor model via particle swarm optimization for high-dimensional and sparse matrices 会议论文
2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019, Bari, Italy, October 6, 2019 - October 9, 2019
作者:  Chen, Sili;  Yuan, Ye;  Wang, Jin
收藏  |  浏览/下载:147/0  |  提交时间:2020/02/18
Distinguishing two phenotypes of blooms using the normalised difference peak-valley index (NDPI) and Cyano-Chlorophyta index (CCI) 期刊论文
SCIENCE OF THE TOTAL ENVIRONMENT, 2018, 卷号: 628-629, 页码: 848-857
作者:  Zhou, Botian;  Shang, Mingsheng;  Wang, Guoyin;  Zhang, Sheng;  Feng, Li;  Liu, Xiangnan;  Wu, Ling;  Shan, Kun
Adobe PDF(4522Kb)  |  收藏  |  浏览/下载:253/0  |  提交时间:2018/07/26
Remote Sensing  Cyanobacteria  Green Algae  Normalised Difference Peak-valley Index  Cyano-chlorophyta Index  Three Gorges Reservoir  
Randomized latent factor model for high-dimensional and sparse matrices from industrial applications 会议论文
15th IEEE International Conference on Networking, Sensing and Control, ICNSC 2018, Zhuhai, China, March 27, 2018 - March 29, 2018
作者:  Chen, Jia;  Luo, Xin
Adobe PDF(5259Kb)  |  收藏  |  浏览/下载:130/0  |  提交时间:2019/06/25
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
Adobe PDF(805Kb)  |  收藏  |  浏览/下载:415/0  |  提交时间:2019/06/26
TCR: Temporal-CNN for Reviews Based Recommendation System 会议论文
2nd International Conference on Deep Learning Technologies, ICDLT 2018, Chongqing, China, June 27, 2018 - June 29, 2018
作者:  Mao, Yelu;  Shi, Xiaoyu;  Shang, Ming-Sheng;  Zhang, Ying
Adobe PDF(508Kb)  |  收藏  |  浏览/下载:902/1  |  提交时间:2019/06/25
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  
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  
Remote estimation of cyanobacterial blooms using the risky grade index (RGI) and coverage area index (CAI): a case study in the Three Gorges Reservoir, China 期刊论文
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2017, 卷号: 24, 期号: 23, 页码: 19044-19056
作者:  Zhou, Botian;  Shang, Mingsheng;  Wang, Guoyin;  Feng, Li;  Shan, Kun;  Liu, Xiangnan;  Wu, Ling;  Zhang, Xuerui
Adobe PDF(1790Kb)  |  收藏  |  浏览/下载:141/0  |  提交时间:2018/03/05
Remote sensing  Cyanobacterial blooms  Water optical classification  Density peaks  Risky grade index  Coverage area index  Three Gorges Reservoir