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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 4
977-981,985

Low-rank matrix factorization recommendation model based on double regularization mechanism

Yu Xue1
Zhang Haonan2
1. Dept. of Management & Economics, Tianjin University, Tianjin 300072, China
2. Dept. of Mathematics, Lehigh University, Bethlehem, PA 18015, USA
DOI: 10.19734/j.issn.1001-3695.2018.09.0739

Abstract

Social recommendation based on matrix factorization enhances the learning accuracy by adding user trust relationship, but ignored the influence of related information between items on user interest in the process of model decomposition. This paper first provided an improved item similarity function to measure correlations between items by considering the user frequency factor, and then established a matrix factorization model with two regularization terms, which combined item relations regularization and social regularization into matrix factorization objective function to present the constraints on low rank approximation. It explored a major impact of the item association information on recommendation when optimizing the implicit feature matrix. The experiments on two real-world datasets demonstrate that this method outperforms other state-of-the-art matrix factorization approaches especially dealing with the large sparse data, and effectively alleviates the cold-start user problem.

Foundation Support

国家自然科学基金资助项目(71502125,71671121)
天津大学自主创新基金资助项目(2017XZC-0083)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.09.0739
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 4
Section: Algorithm Research & Explore
Pages: 977-981,985
Serial Number: 1001-3695(2020)04-004-0977-05

Publish History

[2020-04-05] Printed Article

Cite This Article

郁雪, 张昊男. 融合双重正则化机制的低秩矩阵分解推荐模型 [J]. 计算机应用研究, 2020, 37 (4): 977-981,985. (Yu Xue, Zhang Haonan. Low-rank matrix factorization recommendation model based on double regularization mechanism [J]. Application Research of Computers, 2020, 37 (4): 977-981,985. )

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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