Research on big data personalised recommendation model based on deep reinforcement learning

被引:0
|
作者
Shi H. [1 ]
Shang L. [1 ]
机构
[1] School of Network and Communication, Nanjing Vocational College of Information Technology, Nanjing
关键词
deep reinforcement learning; dynamic modelling; effectiveness; personalised recommendation;
D O I
10.1504/IJNVO.2023.133876
中图分类号
学科分类号
摘要
In order to mine the user’s preference and interest from the user’s historical behaviour in the big data to make a personalised recommendation, a DRR model is constructed based on deep reinforcement learning, and the performance of the DRR model is analysed through experiments. The results showed that the DRR model had a higher effect than other comparable models in the offline experimental evaluation, and the DRR-att value was the highest, reaching 0.9025. In the online simulation experiment, the average DRR-att value was the highest reward rate, reaching 0.7466. In general, the DRR model had better analysis ability and strong dynamic modelling ability and was good at using long-term rewards for decision making. In the parameter analysis experiment, the T value reached ten points. At the same time, the user state expression module can improve the accuracy of the DRR model and is effective in actual user personalised recommendations. Copyright © 2023 Inderscience Enterprises Ltd.
引用
收藏
页码:364 / 380
页数:16
相关论文
共 50 条
  • [1] Study on recommendation of personalised learning resources based on deep reinforcement learning
    Li Z.
    Wang H.
    International Journal of Information and Communication Technology, 2023, 23 (04) : 299 - 313
  • [2] Research on Recommendation of Big Data for Higher Education Based on Deep Learning
    Zhao, Ang
    Ma, Yanhua
    SCIENTIFIC PROGRAMMING, 2022, 2022
  • [3] Deep Learning-based Evolutionary Recommendation Model for Heterogeneous Big Data Integration
    Yoo, Hyun
    Chung, Kyungyong
    KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2020, 14 (09) : 3730 - 3744
  • [4] RLISR: A Deep Reinforcement Learning Based Interactive Service Recommendation Model
    Zhang, Mingwei
    Qu, Yingjie
    Li, Yage
    Wen, Xingyu
    Zhou, Yi
    IEEE ACCESS, 2024, 12 : 90204 - 90217
  • [5] A big-data-driven matching model based on deep reinforcement learning for cotton blending
    Xia, Huosong
    Wang, Yuan
    Jasimuddin, Sajjad
    Zhang, Justin Zuopeng
    Thomas, Andrew
    INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2023, 61 (22) : 7573 - 7591
  • [6] Personalised Fashion Recommendation using Deep Learning
    Sonie, Omprakash
    Chelliah, Muthusamy
    Sural, Shamik
    PROCEEDINGS OF THE 6TH ACM IKDD CODS AND 24TH COMAD, 2019, : 368 - 368
  • [7] RESEARCH ON DATA MINING AND REINFORCEMENT LEARNING IN RECOMMENDATION SYSTEMS
    Zhao, Yueran
    Zhao, Huiyan
    SCALABLE COMPUTING-PRACTICE AND EXPERIENCE, 2024, 25 (03): : 1914 - 1922
  • [8] GNN-based deep reinforcement learning for MBD product model recommendation
    Hu, Yuying
    Sheng, Zewen
    Ye, Min
    Zhang, Meiyu
    Jian, Chengfeng
    INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING, 2024, 37 (1-2) : 183 - 197
  • [9] Research on e-commerce personalised transaction processing model based on reinforcement learning
    Chi, Jinling
    International Journal of Computational Systems Engineering, 2023, 7 (2-4) : 77 - 85
  • [10] A personalised recommendation of mobile learning model based on content awareness
    Luo, Yuanyuan
    INTERNATIONAL JOURNAL OF CONTINUING ENGINEERING EDUCATION AND LIFE-LONG LEARNING, 2023, 33 (2-3) : 299 - 312