An Instance-Frequency-Weighted Regularization Scheme for Non-Negative Latent Factor Analysis on High-Dimensional and Sparse Data
文献类型：期刊论文
| 作者 | Luo, Xin4 ; Wang, Zidong1; Shang, Mingsheng2,3
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| 刊名 | IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
 |
| 出版日期 | 2021-06-01 |
| 卷号 | 51期号:6页码:3522-3532 |
| 关键词 | High-dimensional and sparse (HiDS) data industrial application instance-frequency non-negative latent factor analysis (NLFA) recommender system regularization |
| ISSN号 | 2168-2216 |
| DOI | 10.1109/TSMC.2019.2930525 |
| 通讯作者 | Shang, Mingsheng(msshang@cigit.ac.cn) |
| 英文摘要 | High-dimensional and sparse (HiDS) data with non-negativity constraints are commonly seen in industrial applications, such as recommender systems. They can be modeled into an HiDS matrix, from which non-negative latent factor analysis (NLFA) is highly effective in extracting useful features. Preforming NLFA on an HiDS matrix is ill-posed, desiring an effective regularization scheme for avoiding overfitting. Current models mostly adopt a standard L-2 scheme, which does not consider the imbalanced distribution of known data in an HiDS matrix. From this point of view, this paper proposes an instancefrequency-weighted regularization (IR) scheme for NLFA on HiDS data. It specifies the regularization effects on each latent factors with its relevant instance count, i.e., instance-frequency, which clearly describes the known data distribution of an HiDS matrix. By doing so, it achieves finely grained modeling of regularization effects. The experimental results on HiDS matrices from industrial applications demonstrate that compared with an L-2 scheme, an IR scheme enables a resultant model to achieve higher accuracy in missing data estimation of an HiDS matrix. |
| 资助项目 | National Natural Science Foundation of China[61772493] ; National Natural Science Foundation of China[91646114] ; National Natural Science Foundation of China[61602352] ; Chongqing Research Program of Technology Innovation and Application[cstc2017rgzn-zdyfX0020] ; Chongqing Research Program of Technology Innovation and Application[cstc2017zdcyzdyf0554] ; Chongqing Research Program of Technology Innovation and Application[cstc2017rgzn-zdyf0118] ; Chongqing Cultivation Program of Innovation and Entrepreneurship Demonstration Group[cstc2017kjrc-cxcytd0149] ; Chongqing Overseas Scholars Innovation Program[cx2017012] ; Chongqing Overseas Scholars Innovation Program[cx2018011] ; Pioneer Hundred Talents Program of Chinese Academy of Sciences |
| WOS研究方向 | Automation & Control Systems ; Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000652103000018 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/13658]  |
| 专题 | 中国科学院重庆绿色智能技术研究院 |
| 通讯作者 | Shang, Mingsheng |
| 作者单位 | 1.Brunel Univ London, Dept Informat Syst & Comp, Uxbridge UB8 3PH, Middx, England 2.Chinese Acad Sci, Chongqing Engn Res Ctr Big Data Applicat Smart Ci, Chongqing 400714, Peoples R China 3.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing Key Lab Big Data & Intelligent Comp, Chongqing 400714, Peoples R China 4.Dongguan Univ Technol, Sch Comp Sci & Technol, Dongguan 523808, Peoples R China |
| 推荐引用方式 GB/T 7714 | Luo, Xin,Wang, Zidong,Shang, Mingsheng. An Instance-Frequency-Weighted Regularization Scheme for Non-Negative Latent Factor Analysis on High-Dimensional and Sparse Data[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2021,51(6):3522-3532. |
| APA | Luo, Xin,Wang, Zidong,&Shang, Mingsheng.(2021).An Instance-Frequency-Weighted Regularization Scheme for Non-Negative Latent Factor Analysis on High-Dimensional and Sparse Data.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,51(6),3522-3532. |
| MLA | Luo, Xin,et al."An Instance-Frequency-Weighted Regularization Scheme for Non-Negative Latent Factor Analysis on High-Dimensional and Sparse Data".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 51.6(2021):3522-3532. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
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