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Non-Negative Latent Factor Model Based on beta-Divergence for Recommender Systems

文献类型：期刊论文

作者Xin, Luo2; Yuan, Ye1,3,4; Zhou, MengChu5,6; Liu, Zhigang1,3; Shang, Mingsheng1,3
刊名IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
出版日期2021-08-01
卷号51期号:8页码:4612-4623
关键词beta-divergence big data high-dimensional and sparse (HiDS) matrix industrial application learning algorithm non-negative latent factor (NLF) analysis recommender system
ISSN号2168-2216
DOI10.1109/TSMC.2019.2931468
通讯作者Zhou, MengChu(zhou@njit.edu) ; Shang, Mingsheng(msshang@cigit.ac.cn)
英文摘要Non-negative latent factor (NLF) models well represent high-dimensional and sparse (HiDS) matrices filled with non-negative data, which are frequently encountered in industrial applications like recommender systems. However, current NLF models mostly adopt Euclidean distance in their objective function, which represents a special case of a beta-divergence function. Hence, it is highly desired to design a beta-divergence-based NLF (beta-NLF) model that uses a beta-divergence function, and investigate its performance in recommender systems as beta varies. To do so, we first model beta-NLF's learning objective with a beta-divergence function. Subsequently, we deduce a general single latent factor-dependent, non-negative and multiplicative update scheme for beta-NLF, and then design an efficient beta-NLF algorithm. The experimental results on HiDS matrices from industrial applications indicate that by carefully choosing the value of beta, beta-NLF outperforms an NLF model with Euclidean distance in terms of accuracy for missing data prediction without increasing computational time. The research outcomes show the necessity of using an optimal beta-divergence function in order to achieve the best performance of an NLF model on HiDS matrices. Hence, the proposed model has both theoretical and application significance.
资助项目National Natural Science Foundation of China[61772493] ; National Natural Science Foundation of China[91646114] ; National Natural Science Foundation of China[51609229] ; National Natural Science Foundation of China[61872065] ; National Natural Science Foundation of China[61702475] ; National Key Research and Development Program of China[2017YFC0804002] ; Chongqing Cultivation Program of Innovation and Entrepreneurship Demonstration Group[cstc2017kjrc-cxcytd0149] ; Chongqing Overseas Scholars Innovation Program[cx2017012] ; Chongqing Overseas Scholars Innovation Program[cx2018011] ; Chongqing Research Program of Technology Innovation and Application[cstc2017zdcy-zdyfX0076] ; Chongqing Research Program of Technology Innovation and Application[cstc2018jszx-cyztzxX0025] ; Chongqing Research Program of Technology Innovation and Application[cstc2017rgzn-zdyfX0020] ; Chongqing Research Program of Technology Innovation and Application[cstc2017zdcy-zdyf0554] ; Chongqing Research Program of Technology Innovation and Application[cstc2017rgzn-zdyf0118] ; 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:000673624500001
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://119.78.100.138/handle/2HOD01W0/13747]  
专题中国科学院重庆绿色智能技术研究院
通讯作者Zhou, MengChu; Shang, Mingsheng
作者单位1.Chinese Acad Sci, Chongqing Engn Res Ctr Big Data Applicat Smart Ci, Chongqing 400714, Peoples R China
2.Dongguan Univ Technol, Sch Comp Sci & Technol, Dongguan 523808, 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.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
5.New Jersey Inst Technol, Dept Elect & Comp Engn, Newark, NJ 07102 USA
6.King Abdulaziz Univ, Ctr Res Excellence Renewable Energy & Power Syst, Jeddah 21589, Saudi Arabia
推荐引用方式
GB/T 7714		 Xin, Luo,Yuan, Ye,Zhou, MengChu,et al. Non-Negative Latent Factor Model Based on beta-Divergence for Recommender Systems[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2021,51(8):4612-4623.
APA Xin, Luo,Yuan, Ye,Zhou, MengChu,Liu, Zhigang,&Shang, Mingsheng.(2021).Non-Negative Latent Factor Model Based on beta-Divergence for Recommender Systems.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,51(8),4612-4623.
MLA Xin, Luo,et al."Non-Negative Latent Factor Model Based on beta-Divergence for Recommender Systems".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 51.8(2021):4612-4623.

入库方式： OAI收割

来源：重庆绿色智能技术研究院

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