Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 11
3294-3302

Session recommendation method based on global graph diffusion and spatio-temporal awareness disentanglement

Gao Rong1,2
Zhou Hao1
Shao Xiongkai1
Wu Xinyun1
1. School of Computer Science, Hubei University of Technology, Wuhan 430068, China
2. State Key Laboratory of New Computer Software Technology, Nanjing University, Nanjing 210093, China
DOI: 10.19734/j.issn.1001-3695.2023.04.0126

Abstract

To address the problem of insufficient recommendation performance in session recommendation, this paper proposed a disentangled graph neural network model(GDST-GNN) using global graph diffusion and spatio-temporal awareness. Specifically, the model firstly constructed a global collaborative graph based on all sessions from a global perspective, and then employed graph diffusion as the message propagation paradigm for global representation learning of items to capture global information beyond the current session. For the representation learning of the current session, this paper designed a disentangled spatio-temporal gated network modeling the complex transition pattern and temporal dependency pattern of items in the session, and then fused the learned global and local representations factor by factor. In addition, this paper employed a self-supervised task to achieve performance enhancement of the model. Finally, it generated session representations through attention networks to achieve accurate recommendation of items. Extensive experiments on four real-world datasets validate the effectiveness of the proposed model.

Foundation Support

国家自然科学基金资助项目(61902116)
南京大学计算机软件新技术国家重点实验室开放课题(KFKT2021B12)
湖北省高层次人才基金资助项目(GCRC2020011)
湖北工业大学博士科研启动基金资助项目(BSQD2019026,BSQD2019022)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.04.0126
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 11
Section: Algorithm Research & Explore
Pages: 3294-3302
Serial Number: 1001-3695(2023)11-014-3294-09

Publish History

[2023-06-07] Accepted Paper
[2023-11-05] Printed Article

Cite This Article

高榕, 周浩, 邵雄凯, 等. 基于全局图扩散和时空感知的解缠绕会话推荐方法 [J]. 计算机应用研究, 2023, 40 (11): 3294-3302. (Gao Rong, Zhou Hao, Shao Xiongkai, et al. Session recommendation method based on global graph diffusion and spatio-temporal awareness disentanglement [J]. Application Research of Computers, 2023, 40 (11): 3294-3302. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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