Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 5
1302-1304,1310

Linear regression recommendation algorithm with collaborative filtering

Pang Hailong
Zhao Hui
Li Wanlong
Ma Ying
Cui Yan
School of Computer Science & Engineering, Changchun University of Technology, Changchun 130012, China
DOI: 10.19734/j.issn.1001-3695.2017.11.0732

Abstract

This paper proposed a linear regression algorithm to integrate collaborative filtering based on the data sparse influence of the traditional collaborative filtering algorithm. Firstly, it built a similarity matrix between the user and the project based on the user's rating of the project, as well as the user and the project's own characteristics. Secondly, based on the similarity matrix, it selected the user and project nearest neighbor set. It predicted the score that the users had graded respectively by the way of collaborative filtering algorithms based on the user and the project. And it would take the difference between predicted scores and the real scores as features to generate new training data, and regarded the new training data as the input of the linear regression model. Finally, according to the training model, it could predict the unknown score, and used the top-N algorithm to generate the recommended list. It conducted the experiment on the MovieLens data set. The experimental result shows that the proposed accuracy of the new algorithm improves compared with the traditional collaborative filtering algorithm.

Foundation Support

国家自然科学基金资助项目(61472049)
吉林省教育厅“十二五”科学技术研究项目(2014132)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.11.0732
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 5
Section: Algorithm Research & Explore
Pages: 1302-1304,1310
Serial Number: 1001-3695(2019)05-005-1302-03

Publish History

[2019-05-05] Printed Article

Cite This Article

庞海龙, 赵辉, 李万龙, 等. 融合协同过滤的线性回归推荐算法 [J]. 计算机应用研究, 2019, 36 (5): 1302-1304,1310. (Pang Hailong, Zhao Hui, Li Wanlong, et al. Linear regression recommendation algorithm with collaborative filtering [J]. Application Research of Computers, 2019, 36 (5): 1302-1304,1310. )

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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