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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 12
3578-3581,3598

Recommendation algorithm based on filling method and multi-weight similarity

Zou Yang1
Wu Hecheng1
Jiang Yunzhi2
Zhao Yingding3
1. College of Economic & Management, Nanjing University of Aeronautics & Astronautics, Nanjing 211106, China
2. School of Mathematics & Systems Science, Guangdong Polytechnic Normal University, Guangzhou 510540, China
3. College of Software, Jiangxi Agricultural University, Nanchang 330045, China
DOI: 10.19734/j.issn.1001-3695.2019.09.0541

Abstract

In order to solve the problem of data sparsity in traditional recommendation algorithms, many researchers at home and abroad have proposed corresponding recommendation algorithms. However, most of these algorithms have not achieved good recommendation results in personalized recommendation. Therefore, this paper proposed a recommendation algorithm based on improved filling method and multi-weight similarity. Firstly, the algorithm filled missing values and reduced data dimension by improved filling method, then calculated user trust degree and user association degree of bipartite graph respectively, and finally used multi-weight factor to combine the two similarities. Based on this, this algorithm obtained neighbor users according to similarity and made recommendation to target users. The experimental results show that the MAE of proposed algorithm is superior to other recommendation methods in the case of sparse data and personalized recommendation.

Foundation Support

国家自然科学青年基金资助项目(61702118)
广东省教育厅青年创新人才项目(自然科学)(2016KQNCX089)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.09.0541
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 12
Section: Algorithm Research & Explore
Pages: 3578-3581,3598
Serial Number: 1001-3695(2020)12-011-3578-04

Publish History

[2020-12-05] Printed Article

Cite This Article

邹洋, 吴和成, 姜允志, 等. 改进填补法和多权重相似度相结合的推荐算法 [J]. 计算机应用研究, 2020, 37 (12): 3578-3581,3598. (Zou Yang, Wu Hecheng, Jiang Yunzhi, et al. Recommendation algorithm based on filling method and multi-weight similarity [J]. Application Research of Computers, 2020, 37 (12): 3578-3581,3598. )

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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