Analysis of Recommendation Systems Based on Neural Networks

被引:0
|
作者
Song, Ningxin [1 ]
机构
[1] Shanghai Univ Finance & Econ, Dept Stat & Management, Shanghai 200433, Peoples R China
关键词
D O I
10.1088/1742-6596/1634/1/012051
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
As the amount of online information explodes, the recommendation system has evolved into an effective strategy to overcome the problem of information overload, which has become the focus of academic and industrial circles, and has led to other related research results. Through the recommendation methods, the author mines the items including information, service, and goods that the user is interested in, and recommends the results to the user in the form of a personalized list. In this paper, the author mainly examines and summarizes the progress of research on neural network based recommendation systems in recent years, as well as giving conclusions about the differences and benefits between that and traditional algorithms. In the end, the future trend of the recommendation systems based on neural networks is prospected.
引用
收藏
页数:7
相关论文
共 50 条
  • [31] SimGNN: simplified graph neural networks for session-based recommendation
    Tajuddeen Rabiu Gwadabe
    Mohammed Ali Mohammed Al-hababi
    Ying Liu
    Applied Intelligence, 2023, 53 : 22789 - 22802
  • [32] POI recommendation for random groups based on cooperative graph neural networks
    Liu, Zhizhong
    Meng, Lingqiang
    Sheng, Quan Z.
    Chu, Dianhui
    Yu, Jian
    Song, Xiaoyu
    INFORMATION PROCESSING & MANAGEMENT, 2024, 61 (03)
  • [33] ABP neural networks-based collaborative filtering recommendation algorithm
    Zhang, Lei
    Chen, Jun-Liang
    Meng, Xiang-Wu
    Shen, Xiao-Yan
    Duan, Kun
    Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications, 2009, 32 (06): : 42 - 46
  • [34] Learning Path Recommendation System for Programming Education Based on Neural Networks
    Saito, Tomohiro
    Watanobe, Yutaka
    INTERNATIONAL JOURNAL OF DISTANCE EDUCATION TECHNOLOGIES, 2020, 18 (01) : 36 - 64
  • [35] A Recommendation System for CAD Assembly Modeling Based on Graph Neural Networks
    Gajek, Carola
    Schiendorfer, Alexander
    Reif, Wolfgang
    MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2022, PT I, 2023, 13713 : 457 - 473
  • [36] LGRec:A group recommendation method based on graph convolutional neural networks
    Jiang, Pingsheng
    Lin, Bing
    Zhang, Xun
    2024 9TH INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATION SYSTEMS, ICCCS 2024, 2024, : 1343 - 1349
  • [37] Attentive Capsule Graph Neural Networks for Session-Based Recommendation
    Chen, Yingpei
    Tang, Yan
    KNOWLEDGE SCIENCE, ENGINEERING AND MANAGEMENT, PT I, 2022, 13368 : 602 - 613
  • [38] Graph and Sequential Neural Networks in Session-based Recommendation: A Survey
    Li, Zihao
    Yang, Chao
    Chen, Yakun
    Wang, Xianzhi
    Chen, Hongxu
    Xu, Guandong
    Yao, Lina
    Sheng, Michael
    ACM COMPUTING SURVEYS, 2025, 57 (02)
  • [39] An Efficient Group Recommendation Model With Multiattention-Based Neural Networks
    Huang, Zhenhua
    Xu, Xin
    Zhu, Honghao
    Zhou, MengChu
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 31 (11) : 4461 - 4474
  • [40] POI recommendation for occasional groups Based on hybrid graph neural networks
    Meng, Lingqiang
    Liu, Zhizhong
    Chu, Dianhui
    Sheng, Quan Z.
    Yu, Jian
    Song, Xiaoyu
    EXPERT SYSTEMS WITH APPLICATIONS, 2024, 237