Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 2
456-462

Item associations aware multi-interest sequential recommendation method

Zhang Jiea
Chen Kejiaa,b
a. School of Computer Science, b. Jiangsu Key Laboratory of Big Data Security & Intelligent Processing, Nanjing University of Posts & Telecommunications, Nanjing 210023, China
DOI: 10.19734/j.issn.1001-3695.2022.06.0333

Abstract

Existing sequential recommendation methods based on multi-interest frameworks only learn the multi-interest representations from users' recent interaction sequences, ignoring the association information between items in the dataset. To address this problem, this paper proposed an item associations aware multi-interest sequential recommendation method(IAMIRec). Firstly, this method obtained the item association set and matrix by calculating the user's interaction sequence in the dataset, then modeled the user's recent interaction sequence by the association martix and the multi-head self-attention mechanism, and used the multi-interest framework to model the user's multiple interest vectors. It used the obtained multiple interest vectors to the top-N recommendation for users. This paper tested and analyzed the model on three datasets, IAMIRec outperformed related methods on recall, NDCG, and hit rate metrics. The results show that IAMIRec can achieve better recommendation performance, and also show that it can effectively enhance the multi-interest representation of users through item associations information.

Foundation Support

国家自然科学基金资助项目(61876091)
南京邮电大学校级科研基金资助项目(NY221071)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.06.0333
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 2
Section: Algorithm Research & Explore
Pages: 456-462
Serial Number: 1001-3695(2023)02-024-0456-07

Publish History

[2022-09-23] Accepted Paper
[2023-02-05] Printed Article

Cite This Article

张杰, 陈可佳. 关联项目增强的多兴趣序列推荐方法 [J]. 计算机应用研究, 2023, 40 (2): 456-462. (Zhang Jie, Chen Kejia. Item associations aware multi-interest sequential recommendation method [J]. Application Research of Computers, 2023, 40 (2): 456-462. )

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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