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Algorithm Research & Explore
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2640-2644,2683

Collaborative filtering recommendation algorithm based on multi-attribute dynamic sampling

Li Weiqian1,2,3
Zhang Yi1,2,3
Zheng Zhenfeng4
Wang Hai5
Zhang Ziyun1,2,3
1. School of Computer Science, Xi'an Polytechnic University, Xi'an 710048, China
2. Shaanxi Key Laboratory of Clothing Intelligence, Xi'an 710048, China
3. State & Local Joint Engineering Research Center for Advanced Networking & Intelligent Information Services, Xi'an 710048, China
4. School of Electronic Engineering, Shaanxi Institute of Technology, Xi'an 710300, China
5. School of Information & Technology, Northwest University, Xi'an 710127, China

Abstract

Aiming at the problem that the recommendation accuracy of collaborative filtering recommendation algorithm and the matching degree of user data in the algorithm are not high at present, this paper proposed a multi-attribute conditional restricted Boltzmann machine collaborative filtering recommendation model(MA-CRBM). The model was based on the conditional Boltzmann machine of real value state, which integrated the attributes of users' occupation and gender, and mode full use of the potential scoring and unscoring information in the data set. In the training process, it adopted the multi-step iterative dynamic sampling algorithm to improve the original sampling algorithm, which overcame the problem of low accuracy caused by too large fluctuation of data sampling error in the later training period. The experimental results on MovieLens data set show that the MA-CRBM model has a good recommendation effect and can effectively improve the accuracy and efficiency of the recommendation model.

Foundation Support

国家自然科学基金资助项目(61572401,61672426,61701400)
西安工程大学博士科研启动基金资助项目(BS1330)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.04.0124
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 9
Section: Algorithm Research & Explore
Pages: 2640-2644,2683
Serial Number: 1001-3695(2020)09-015-2640-05

Publish History

[2020-09-05] Printed Article

Cite This Article

李维乾, 张艺, 郑振峰, 等. 基于多属性的动态采样协同过滤推荐算法 [J]. 计算机应用研究, 2020, 37 (9): 2640-2644,2683. (Li Weiqian, Zhang Yi, Zheng Zhenfeng, et al. Collaborative filtering recommendation algorithm based on multi-attribute dynamic sampling [J]. Application Research of Computers, 2020, 37 (9): 2640-2644,2683. )

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.

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