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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 7
1979-1982

Research on learning resource recommendation algorithm based on behavior sequence analysis

Gui Zhongyan
Zhang Yanming
Li Weiwei
College of Medical Information Engineering, Heilongjiang University of Chinese Medicine, Harbin 150040, China
DOI: 10.19734/j.issn.1001-3695.2018.12.0930

Abstract

Using the data mining technology to analyze the network learning behavior data can dig out its hidden behavior characteristics, and provide personalized learning resource services for learners. Aiming at the problem that the model applicability of the existing data mining algorithms generally was not very high when analyzing of network learning behavior data, this paper proposed a learning resource recommendation algorithm based on behavior sequence analysis. Firstly, this paper proposed the definition of behavior sequence and its related concepts. Secondly, it proposed the calculation method of behavior sequence similarity. Then, it proposed the collaborative filtering recommendation algorithm based on behavioral sequence similarity to calculate the similarity between learners and to generate the learning resource recommendation list for the learner to be recommended. And then it gave the recommendation algorithm based on learning style, and integrated learners' learning style characteristics into the recommendation process. Finally, it presented the learning resource recommendation algorithm based on behavior sequence analysis. The proposed algorithm does not limit the pattern of behavior sequence, and has a high applicability, it can be used for further study of the network learning behavior data and provide personalized learning service for learners.

Foundation Support

黑龙江中医药大学教育教学研究项目(XJJY2018028)
黑龙江省高等教育教学改革研究一般研究项目(SJGY20180486)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.12.0930
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 7
Section: Algorithm Research & Explore
Pages: 1979-1982
Serial Number: 1001-3695(2020)07-012-1979-04

Publish History

[2020-07-05] Printed Article

Cite This Article

桂忠艳, 张艳明, 李巍巍. 基于行为序列分析的学习资源推荐算法研究 [J]. 计算机应用研究, 2020, 37 (7): 1979-1982. (Gui Zhongyan, Zhang Yanming, Li Weiwei. Research on learning resource recommendation algorithm based on behavior sequence analysis [J]. Application Research of Computers, 2020, 37 (7): 1979-1982. )

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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