In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) will be discontinued after Dec. 31st, 2024.
See More
Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 5
1371-1375,1380

Sequential recommendation model that combines self-attention mechanism with long-term and short-term preferences

Shen Xuelia
Du Zhiweib
a. School of Software, b. School of Electronic & Information Engineering, Liaoning Technical University, Huludao Liaoning 125105, China
DOI: 10.19734/j.issn.1001-3695.2020.05.0121

Abstract

In order to solve the problem that the existing sequence recommendation algorithms only use short-term sequential behaviors to make recommendations, but fail to fully consider the long-term preference of users and the deeper relationship between items, this paper proposed a sequential recommendation algorithm CSALSR that it integrated self-attention mechanism and long-term and short-term preference. This model embedded the user and the item into the vector respectively, and regarded the pairwise encoding of the item in short-term interaction sequence as a three-way tensor. Then, it added self-attention mechanism on the three-way tensor and used convolutional neural network to extract the deeper connection between items from the order pattern of users. At the same time, considering the long-term preference of users, it took the embedding of similar users as a supplement to enhance the user representation. Experimental results show that the proposed method on MovieLens-1M and Gowalla data sets is superior to other methods in precision@N, recall@N and MAP.

Foundation Support

国家自然科学基金资助项目(61772249)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.05.0121
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 5
Section: Algorithm Research & Explore
Pages: 1371-1375,1380
Serial Number: 1001-3695(2021)05-016-1371-05

Publish History

[2021-05-05] Printed Article

Cite This Article

沈学利, 杜志伟. 融合自注意力机制与长短期偏好的序列推荐模型 [J]. 计算机应用研究, 2021, 38 (5): 1371-1375,1380. (Shen Xueli, Du Zhiwei. Sequential recommendation model that combines self-attention mechanism with long-term and short-term preferences [J]. Application Research of Computers, 2021, 38 (5): 1371-1375,1380. )

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.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)