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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 9

Graph sampling based recommendation model for diversity needs awareness

Xu Jianmin1
Lu Ping1
Zhang Xiongtao2,3
1. School of Cyber Security & Computer, Hebei University, Baoding Hebei 071000, China
2. School of Information Management, Nanjing University, Nanjing Jiangsu 210000, China
3. School of Management, Hebei University, Baoding Hebei 071000, China
DOI: 10.19734/j.issn.1001-3695.2025.03.0045

Abstract

Existing diversified recommendation methods ignore individual diversity needs differences, causing insufficient adaptation of recommendation diversity. To address this issue, this study proposed a graph sampling based recommendation model for diversity needs awareness. The method achieved personalized recommendation diversity by perceiving diversity needs intensity and optimizing graph structures. It first quantified users' diversity needs intensity through time-decay weighted item dissimilarity. Secondly, the method developed an adaptive graph sampling strategy based on needs intensity, determining sampling frequency according to users' diversity needs levels. It applied a greedy algorithm to iteratively select nodes with the highest neighborhood dissimilarity, constructing a diversity-aware subgraph for graph learning. Then, the model used a graph neural network to learn the diverse interest representations of users from the diversity needs-aware subgraph. Finally, the model predicted the interaction probability between users and items through dot product operations and generated diversified recommendations. The experimental part used two public datasets for verification. The proposed model improved accuracy metrics by approximately 3% and diversity metrics by 5%. These results demonstrate that incorporating users' diversity needs effectively achieves a better accuracy-diversity trade-off.

Foundation Support

国家社会科学基金资助项目(23BTQ092)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.03.0045
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 9

Publish History

[2025-05-22] Accepted Paper

Cite This Article

徐建民, 鲁平, 张雄涛. 基于图采样的多样性需求感知推荐模型 [J]. 计算机应用研究, 2025, 42 (9). (2025-05-27). https://doi.org/10.19734/j.issn.1001-3695.2025.03.0045. (Xu Jianmin, Lu Ping, Zhang Xiongtao. Graph sampling based recommendation model for diversity needs awareness [J]. Application Research of Computers, 2025, 42 (9). (2025-05-27). https://doi.org/10.19734/j.issn.1001-3695.2025.03.0045. )

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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