Special Topics in Recommendation Algorithm
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App. Res. of Comp. Printed Article
Vol. 42, 2025 No. 11
3284-3290

Recommendation method based on rating prediction and graph model diffusion

Wang Liua,b,c
Chen Xuebina,b,c
Gao Yuana,b,c
Ma Kaiguanga,b,c
Zhao Tonga,b,c
a. College of Science, b. Hebei Province Key Laboratory of Data Science and Application, c. Tangshan Key Laboratory of Data Science, North China University of Science and Technology, Tangshan Hebei 063210, China
DOI: 10.19734/j.issn.1001-3695.2025.03.0095

Abstract

To address the issues of data sparsity and limited recommendation scope in collaborative filtering algorithms, this paper proposed a recommendation method based on rating prediction and graph model diffusion, named SIRR. Firstly, it designed a dynamic switching mechanism based on the number of user ratings to predict ratings for unrated items, aiming to address the data sparsity problem. Secondly, it improved the accuracy of similarity computation and the robustness of the collaborative filtering algorithm using regularized cosine similarity. Finally, to overcome the limitation of localized recommendations, it applied a weighted random walk on the graph to expand the recommendation scope, enhancing coverage. To balance recommendation accuracy and diversity, it achieved an optimization by integrating rating weights. It validated the effectiveness of regularized cosine similarity on two datasets of different types. The proposed method was compared with three baseline algorithms on three datasets with varying sparsity levels. Simulation results show that SIRR performs well across all evaluation metrics. It provides an effective solution to data sparsity and local recommendation problems.

Foundation Support

国家自然科学基金资助项目(U20A20179)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.03.0095
Publish at: Application Research of Computers Printed Article, Vol. 42, 2025 No. 11
Section: Special Topics in Recommendation Algorithm
Pages: 3284-3290
Serial Number: 1001-3695(2025)11-010-3284-07

Publish History

[2025-07-03] Accepted Paper
[2025-11-05] Printed Article

Cite This Article

王柳, 陈学斌, 高远, 等. 基于评分预测与图模型扩散的推荐方法 [J]. 计算机应用研究, 2025, 42 (11): 3284-3290. (Wang Liu, Chen Xuebin, Gao Yuan, et al. Recommendation method based on rating prediction and graph model diffusion [J]. Application Research of Computers, 2025, 42 (11): 3284-3290. )

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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.

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