In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) has been redirecting to new domain since Jan. 1st, 2025.
See More
App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 12

Social Heterogeneous knowledge guided multi-behavior sequential recommendation method

Li Qingqing
Chen Lei
College of Information Science & Technology, Gansu Agricultural University, Lanzhou Gansu 730070, China
DOI: 10.19734/j.issn.1001-3695.2025.05.0133

Abstract

The existing sequential recommendation methods often overlook the social influence among users and fail to incorporate the multi-behavior information of user interaction. At the same time, they typically lack accurate modeling of complex temporal dynamic features guided by social relationships, including both users' historical habits and dynamic needs. To address these challenges, this paper designed a Social Heterogeneous Knowledge guided Multiple Behavior Sequence Recommendation method (SHKM-SR) . Specifically, the method first integrated temporal interaction information with social relationships to construct a social heterogeneous temporal knowledge graph. Then, it encoded heterogeneous interactions with temporal signals and extracted high-order social-aware representations of nodes. Again, under the guidance of social relationships, the model captured both dynamic characteristics and historical habits of nodes. It further integrated long and short-term preferences of social-aware preferences based on attention mechanism to obtain finer grained representations. Finally, a multi-layer perceptron was employed to calculate item recommendation scores and generate personalized recommendations. The experimental results on Yelp, Ciao and Douban Book datasets show that the method outperforms most benchmark methods, achieving a maximum improvement of 9.6% in Hit@10. The experimental results validate the effectiveness of the model in multi-behavior sequential recommendation.

Foundation Support

甘肃省高校教师创新基金项目(2024B-078)
甘肃省教育科学"十四五"规划2024年度"大学生职业规划与就业指导"专项课题(GS〔2024〕GHBZX0001)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.05.0133
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 12

Publish History

[2025-07-30] Accepted Paper

Cite This Article

李青青, 陈蕾. 社交异构知识引导的多行为序列推荐方法 [J]. 计算机应用研究, 2025, 42 (12). (2025-08-06). https://doi.org/10.19734/j.issn.1001-3695.2025.05.0133. (Li Qingqing, Chen Lei. Social Heterogeneous knowledge guided multi-behavior sequential recommendation method [J]. Application Research of Computers, 2025, 42 (12). (2025-08-06). https://doi.org/10.19734/j.issn.1001-3695.2025.05.0133. )

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)