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App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 12

Graph convolutional recommendation based on adjacency matrix optimization and negative sampling

Wang Hui1
Liang Xingzhu1,2
Zhang Xu1
Xia Chenxing1
1. School of Computer Science & Engineering, Anhui University of Science & Technology, Huainan 232001, China
2. Anhui University of Technology First Affiliated Hospital (Huainan First People's Hospital), Huainan 232007, China
DOI: 10.19734/j.issn.1001-3695.2024.04.0126

Abstract

In order to alleviate the problems of randomly initializing users and items, ignoring the importance of different convolutional layers, and having too few negative samples with low quality in recommendation systems, this paper proposed AMONS. Specifically, the algorithm used adjacency matrix for embedding optimization of users and items, and introduced layer attenuation coefficients in convolutional layer aggregation to distinguish the importance of different layers. Next, it generated a filtered set of negative samples for each pair of user positive samples, allowing the model to fully utilize the historical interaction data between users and items, and better learn user preferences. The experiments were conducted extensively on the Gowalla and Amazon-Books public datasets. Compared to related methods, AMONS achieves the best performance, demonstrating the effectiveness of the method.

Foundation Support

安徽理工大学环境友好材料与职业健康研究院研发专项基金资助项目(ALW2021YF04)
安徽理工大学医学专项培育项目(YZ2023H2C005)
国家自然科学基金资助项目(62102003)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.04.0126
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 12

Publish History

[2024-09-06] Accepted Paper

Cite This Article

王慧, 梁兴柱, 张绪, 等. 基于邻接矩阵优化和负采样的图卷积推荐 [J]. 计算机应用研究, 2024, 41 (12). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.04.0126. (Wang Hui, Liang Xingzhu, Zhang Xu, et al. Graph convolutional recommendation based on adjacency matrix optimization and negative sampling [J]. Application Research of Computers, 2024, 41 (12). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.04.0126. )

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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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