Algorithm Research & Explore
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1024-1029

Recommendation method based on dynamic bipartite network representation learning

Zhang Yangyanga
Chen Kejiaa,b
Zhang Jiea
a. School of Computer Science, b. Jiangsu Key Laboratory of Big Data Security & Intelligent Processing, Nanjing University of Posts & Telecommunications, Nanjing 210023, China

Abstract

Representation learning of a user-item interaction network becomes an effective recommendation method. Most of the existing methods regard the interaction network as a static homogeneous network, ignoring the impact of interaction timing and node heterogeneity. In response to this problem, this paper proposed a recommendation method based on dynamic bipartite network representation learning. Firstly, the method constructed a time-series weighted bipartite network, and then respectively mapped user nodes and item nodes to different vector spaces to preserve the heterogeneity of the network, and aggregated the first-order and high-order neighbor information for center nodes with graph convolution. Finally it used a multi-layer perceptron to learn the nonlinear relationship between the two types of node embeddings and performed top-N recommendation. Experimental results on Amazon and Taobao datasets show that the proposed method is significantly superior than the related methods based on static or heterogeneous network representation learning in HR and NDCG indicators.

Foundation Support

国家自然科学基金面上项目(61772284,61876091)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.09.0409
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 4
Section: Algorithm Research & Explore
Pages: 1024-1029
Serial Number: 1001-3695(2022)04-011-1024-06

Publish History

[2021-12-07] Accepted Paper
[2022-04-05] Printed Article

Cite This Article

张阳阳, 陈可佳, 张杰. 基于动态二分网络表示学习的推荐方法 [J]. 计算机应用研究, 2022, 39 (4): 1024-1029. (Zhang Yangyang, Chen Kejia, Zhang Jie. Recommendation method based on dynamic bipartite network representation learning [J]. Application Research of Computers, 2022, 39 (4): 1024-1029. )

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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