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Research on the evaluation index system of college students’ class teaching quality based on association algorithm

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Abstract

Nowadays, the universal application and development of computer technology make data mining play an extremely crucial role in students’ English education. In this paper, students’ English learning is taken as an entry point, and Apriori algorithm is used to analyze English majors’ education technical to train data mining. In this paper, the introduction of lift-measure interest independent is used to explore the rules that can arouse our own interest. Taking the mutual exclusion of mining data into account, optimize and improve the classic Apriori algorithm, it improves the efficiency of mining frequent item sets effectively. After optimization, AD-apriori algorithm can make the reduction in complexity of time and space in mining process.

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Authors and Affiliations

  1. Hebei University of Engineering, Handan, China

    ZhiChao Wang

  2. Xiaqing School of Media of Handan University, Handan, China

    Qing Tian

  3. School of Public Policy & Management in China University of Mining & Technology, Handan, China

    Xinxing Duan

Authors
  1. ZhiChao Wang
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  2. Qing Tian
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  3. Xinxing Duan
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Corresponding author

Correspondence to Xinxing Duan.

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Wang, Z., Tian, Q. & Duan, X. Research on the evaluation index system of college students’ class teaching quality based on association algorithm. Cluster Comput 22 (Suppl 6), 13797–13803 (2019). https://doi.org/10.1007/s10586-018-2100-8

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  • DOI: https://doi.org/10.1007/s10586-018-2100-8

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