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System Development & Application
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 3
855-860

New improvement and implementation of hybrid collaborative filtering algorithm based on Spark platform

Wang Yuanlong1
Sun Weizhen1
Xiang Yong2
1. Dept. of Computer Science & Technology, College of Information Engineering, Capital Normal University, Beijing 100048, China
2. Dept. of Computer Science & Technology, Tsinghua University, Beijing 100084, China
DOI: 10.19734/j.issn.1001-3695.2017.10.0933

Abstract

Aiming at optimizing and improving a hybrid collaborative filtering based on Spark platform for its sparsity, scalability and personalized recommendation by using the method of algorithm integration, this paper took the model of Stacking integration to integrate multiple weak recommender units in a linearly weighted into a comprehensive recommender. Firstly, this algorithm optimized the collaborative filtering based on the nearest neighbor by presorting and adjusting the similarity calculation strategy with popularity and praise degree, and improved the rationality and complexity of similarity calculation. It solved the problem of score sparsity to some extent. At the same time, this algorithm integrated closely distributed computing platform, which could make full use of the advantages of distributed platform to design and implement an increment iterative model of recommendation algorithm by using the Spark streaming and distributed storage structure. It solved the problem that collaborative filtering algorithm was hard to expand and made poor real-time performance. The experimental data used UCI public data set named MovieLens and NetFlix films' score. The experimental results show that the improved algorithm has a good performance and makes great progress in personalized recommendation, accuracy and scalability compared with the previous algorithms. It provides a feasible algorithm integration scheme for the application of the recommended system.

Foundation Support

北京市教委科技计划项目(KM201310028014)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.10.0933
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 3
Section: System Development & Application
Pages: 855-860
Serial Number: 1001-3695(2019)03-042-0855-06

Publish History

[2019-03-05] Printed Article

Cite This Article

王源龙, 孙卫真, 向勇. 基于Spark的混合协同过滤算法改进与实现 [J]. 计算机应用研究, 2019, 36 (3): 855-860. (Wang Yuanlong, Sun Weizhen, Xiang Yong. New improvement and implementation of hybrid collaborative filtering algorithm based on Spark platform [J]. Application Research of Computers, 2019, 36 (3): 855-860. )

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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