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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：444/0  |  提交时间：2019/12/03
Big Data  QoS prediction  Temporal-aware QoS prediction  Stochastic gradient descent  Latent factorization of tensors  Momentum method  
A data-aware latent factor model for web service Qos prediction 会议论文
23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2019, Macau, China, April 14, 2019 - April 17, 2019
作者:  Wu, Di;  Luo, Xin;  Shang, Mingsheng;  He, Yi;  Wang, Guoyin;  Wu, Xindong
收藏  |  浏览/下载：167/0  |  提交时间：2020/02/18
Popularity and Novelty Dynamics in Evolving Networks 期刊论文
SCIENTIFIC REPORTS, 2018, 卷号: 8, 页码: 10
作者:  Abbas, Khushnood;  Shang, Mingsheng;  Abbasi, Alireza;  Luo, Xin;  Xu, Jian Jun;  Zhang, Yu-Xia
Adobe PDF(2105Kb)  |  收藏  |  浏览/下载：265/0  |  提交时间：2018/06/04
A Highly Accurate Framework for Self-Labeled Semisupervised Classification in Industrial Applications 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 卷号: 14, 期号: 3, 页码: 909-920
作者:  Wu, Di;  Luo, Xin;  Wang, Guoyin;  Shang, Mingsheng;  Yuan, Ye;  Yan, Huyong
收藏  |  浏览/下载：212/0  |  提交时间：2018/06/04
Differential evolution (DE)  general framework  industrial application  positioning optimization  self-labeled  semi-supervised classification (SSC)  
Self-training semi-supervised classification based on density peaks of data 期刊论文
NEUROCOMPUTING, 2018, 卷号: 275, 页码: 180-191
作者:  Wu, Di;  Shang, Mingsheng;  Luo, Xin;  Xu, Ji;  Yan, Huyong;  Deng, Weihui;  Wang, Guoyin
收藏  |  浏览/下载：165/0  |  提交时间：2018/03/05
Density peaks  Self-training  Semi-supervised classification  Supervised learning  
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：414/0  |  提交时间：2019/06/26
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：106/0  |  提交时间：2018/03/05
Learning system  Recommender system  One-step recommendation  Long-term effect  Temporally evolving system  Bipartite network  
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：426/0  |  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：100/0  |  提交时间：2018/03/05
Novelty  Evolving networks  Recommender systems  E-commerce  Collective behaviour  Trend prediction  Emerging behaviour  
Efficient extraction of non-negative latent factors from high-dimensional and sparse matrices in industrial applications 会议论文
16th IEEE International Conference on Data Mining, ICDM 2016, Barcelona, Catalonia, Spain, December 12, 2016 - December 15, 2016
作者:  Luo, Xin;  Shang, Mingsheng;  Li, Shuai
收藏  |  浏览/下载：55/0  |  提交时间：2018/03/16