Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 9
2688-2693

Multi-behavior multi-task recommendation algorithm integrating self-supervised learning enhancement

Shen Xueli
Zhang Rongkai
College of Software, Liaoning Technical University, Huludao Liaoning 125105, China
DOI: 10.19734/j.issn.1001-3695.2023.02.0030

Abstract

To solve the problems of multi-behavior recommendation research such as failing to comprehensively capture multi-behavior interaction features and ignoring a large number of noise labels present in implicit feedback data such as clicks, this paper proposed a multi-behavior multi-task recommendation algorithm integrating self-supervised learning enhancement. Firstly, it sensed the multi-behavior interaction features from both behavior influence weights and behavior implicit semantics, and fused the features into the embedding propagation process to enhance the expressiveness of node embeddings. Then, it constructed the self-supervised learning assistance task to avoid model overfitting to noisy labels through multi-view comparison learning. Finally, it combined the supervised multi-behavior recommendation task the self-supervised learning assistance task and used a multi-objective loss optimization strategy for multi-task learning to obtain more accurate user and item embeddings. The experimental analysis shows that the algorithm has a certain improvement in both HR and NDCG indexes compared with the comparison algorithm, which proves the effectiveness and superiority of the algorithm.

Foundation Support

国家自然科学基金资助项目(62173171)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.02.0030
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 9
Section: Algorithm Research & Explore
Pages: 2688-2693
Serial Number: 1001-3695(2023)09-020-2688-06

Publish History

[2023-04-18] Accepted Paper
[2023-09-05] Printed Article

Cite This Article

沈学利, 张荣凯. 联合自监督学习强化的多行为多任务推荐算法 [J]. 计算机应用研究, 2023, 40 (9): 2688-2693. (Shen Xueli, Zhang Rongkai. Multi-behavior multi-task recommendation algorithm integrating self-supervised learning enhancement [J]. Application Research of Computers, 2023, 40 (9): 2688-2693. )

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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