Journal of Shandong University(Engineering Science) ›› 2025, Vol. 55 ›› Issue (1): 24-29.doi: 10.6040/j.issn.1672-3961.0.2023.285

• Machine Learning & Data Mining • Previous Articles    

Algorithmic acceleration of matrix factorization based recommendation system

DUAN Shengyu1, WU Yining1, SAI Gaole2   

  1. 1. School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China;
    2. College of Integrated Circuits and Optoelectronic Chips, Shenzhen Technology University, Shenzhen 518118, Guangdong, China
  • Published:2025-02-20

PDF (PC)

35

CLC Number: 

  • TP391
[1] Amazon Web Services Inc. Amazon personalize[EB/OL].(2023-12-16)[2023-02-16]. https://aws.amazon.com/personalize/.
[2] COVINGTON P, ADAMS J, SARGI E. Deep neural networks for YouTube recommendations[C] //Proceedings of the 10th Conference on Recommender Systems. New York, USA: ACM, 2016: 191-198.
[3] 王磊,熊于宁,李云鹏,等. 一种基于增强图卷积神经网络的协同推荐模型[J]. 计算机研究与发展, 2021, 58(9): 1987-1996. WANG Lei, XIONG Yuning, LI Yunpeng, et al. A collaborative recommendation model based on enhanced graph convolutional neural network[J]. Journal of Computer Research and Development, 2021, 58(9): 1987-1996.
[4] HE Xiangnan, LIAO Lizi, ZHANG Hanwang, et al. Neural collaborative filtering[C] //Proceedings of the 26th International Conference on World Wide Web. New York, USA: ACM, 2017: 173-182.
[5] RESNICK P, VARIAN H R. Recommender systems[J]. Communications of the ACM, 1997, 40(3): 56-58.
[6] SALAKHUTDINOV R, MNIH A. Probabilistic matrix factorization[C] //Proceedings of the 20th International Conference on Neural Information Processing Systems. New York, USA: ACM, 2007: 1257-1264.
[7] KOREN Y. Factor in the neighbors: Scalable and accurate collaborative filtering[J]. ACM Transactions on Knowledge Discovery from Data, 2010, 4(1): 1-24.
[8] KOREN Y, BELL R, VOLINSKY C. Matrix factorization techniques for recommender systems[J]. Computer, 2009, 42(8): 30-37.
[9] YUE Xiaochen, LIU Qicheng. Parallel algorithms of improved FunkSVD based on GPU[J]. IEEE Access, 2022, 10: 26002-26010.
[10] BOTTOU L. Large-scale machine learning with stochastic gradient descent[C] //Proceedings of the 19th International Conference on Computational Statistics. Berlin, Germany: Springer, 2010: 177-186.
[11] YU H F, HSIEH C J, SI S, et al. Scalable coordinate descent approaches to parallel matrix factorization for recommender systems[C] //12th International Con-ference on Data Mining. New Jersey, USA: IEEE, 2012: 765-774.
[12] CHIN W S, ZHUANG Y, JUAN Y C, et al. A fast parallel stochastic gradient method for matrix factorization in shared memory systems[J]. ACM Transactions on Intelligent Systems and Technology, 2015, 6(1): 1-24.
[13] TAN Wei, CAO Liangliang, FONG L. Faster and cheaper: parallelizing large-scale matrix factorization on GPUs[C] //Proceedings of the 25th International Symposium on High-Performance Parallel and Distributed Computing. New York, USA: ACM, 2016: 219-230.
[14] WEI Feng, GUO Hao, CHENG Shaoyin, et al. AALRSMF: An adaptive learning rate schedule for matrix factorization[C] //Asia-Pacific Web Conference. Berlin, Germany: Springer, 2016: 410-413.
[15] XIE X L, TAN W, FONG L, et al. Cumf_sgd: parallelized stochastic gradient descent for matrix factorization on GPUs[C] //Proceedings of the 26th International Symposium on High-Performance Parallel and Distributed Computing. New York, USA: ACM, 2017: 79-92.
[16] LIAN Xiangru, YUAN Binhang, ZHU Xuefeng, et al. Persia: an open, hybrid system scaling deep learning-based recommenders up to 100 trillion parameters[C] // Proceedings of the 28th SIGKDD Conference on Knowledge Discovery and Data Mining. New York, USA: ACM, 2022: 3288-3298.
[17] DONÀ J, GALLINARI P. Differentiable feature selection, a reparameterization approach[C] //Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference. Berlin, Germany: Springer, 2021: 13-17.
[18] WU Yining, SAI Gaole, DUAN Shengyu. Work-in-Progress: Accelerated matrix factorization by approximate computing for recommendation system[C] //International Conference on Embedded Software. Shanghai, China: IEEE, 2022: 1-2.
[19] HARPER F M, KONSTAN J A. The MovieLens datasets: history and context[J]. ACM Transactions on Interactive Intelligent Systems, 2016, 5(4): 1-19.
[20] CHIN W S, YUAN B W, YANG M Y, et al. LIBMF: a library for parallel matrix factorization in shared-memory systems[J]. Journal of Machine Learing Research, 2016, 17(1): 2971-2977.
[1] LI Erchao, ZHANG Zhizhao. Online dynamic demand vehicle routing planning [J]. Journal of Shandong University(Engineering Science), 2024, 54(5): 62-73.
[2] YANG Jucheng, WEI Feng, LIN Liang, JIA Qingxiang, LIU Jianzheng. A research survey of driver drowsiness driving detection [J]. Journal of Shandong University(Engineering Science), 2024, 54(2): 1-12.
[3] XIAO Wei, ZHENG Gengsheng, CHEN Yujia. Named entity recognition method combined with self-training model [J]. Journal of Shandong University(Engineering Science), 2024, 54(2): 96-102.
[4] Gang HU, Lemeng WANG, Zhiyu LU, Qin WANG, Xiang XU. Importance identification method based on multi-order neighborhood hierarchical association contribution of nodes [J]. Journal of Shandong University(Engineering Science), 2024, 54(1): 1-10.
[5] Jiachun LI,Bowen LI,Jianbo CHANG. An efficient and lightweight RGB frame-level face anti-spoofing model [J]. Journal of Shandong University(Engineering Science), 2023, 53(6): 1-7.
[6] Yujiang FAN,Huanhuan HUANG,Jiaxiong DING,Kai LIAO,Binshan YU. Resilience evaluation system of the old community based on cloud model [J]. Journal of Shandong University(Engineering Science), 2023, 53(5): 1-9, 19.
[7] Ying LI,Jiankun WANG. The classification of mild cognitive impairment based on supervised graph regularization and information fusion [J]. Journal of Shandong University(Engineering Science), 2023, 53(4): 65-73.
[8] YU Yixuan, YANG Geng, GENG Hua. Multimodal hierarchical keyframe extraction method for continuous combined motion [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 42-50.
[9] ZHANG Hao, LI Ziling, LIU Tong, ZHANG Dawei, TAO Jianhua. A technology prediction model based on fuzzy Bayesian networks with sociological factors [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 23-33.
[10] WU Yanli, LIU Shuwei, HE Dongxiao, WANG Xiaobao, JIN Di. Poisson-gamma topic model of describing multiple underlying relationships [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 51-60.
[11] YU Mingjun, DIAO Hongjun, LING Xinghong. Online multi-object tracking method based on trajectory mask [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 61-69.
[12] HUANG Huajuan, CHENG Qian, WEI Xiuxi, YU Chuchu. Adaptive crow search algorithm with Jaya algorithm and Gaussian mutation [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 11-22.
[13] LIU Fangxu, WANG Jian, WEI Benzheng. Auxiliary diagnosis algorithm for pediatric pneumonia based on multi-spatial attention [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 135-142.
[14] LIU Xing, YANG Lu, HAO Fanchang. Finger vein image retrieval based on multi-feature fusion [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 118-126.
[15] Yue YUAN,Yanli WANG,Kan LIU. Named entity recognition model based on dilated convolutional block architecture [J]. Journal of Shandong University(Engineering Science), 2022, 52(6): 105-114.
Viewed
Full text
35
HTML PDF
Just accepted Online first Issue Just accepted Online first Issue
0 0 0 0 0 35

  From local
  Times 35
  Rate 100%

Abstract
79
Just accepted Online first Issue
0 0 79
  From Others
  Times 79
  Rate 100%

Cited
Web of Science  Crossref   ScienceDirect  Search for Citations in Google Scholar >>
 
This page requires you have already subscribed to WoS.
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright 2018 © Editorial office of Journal of Shandong University (Engineering Science)
Supported by Beijing Magtech Co.Ltd