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Application of Improved Association Rule Algorithm in E-commerce English

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Application of Big Data, Blockchain, and Internet of Things for Education Informatization (BigIoT-EDU 2022)

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Abstract

The application of the improved association rule algorithm in E-business English is to find the relationship between the two terms. It can be used to find out the similarities between the two projects, and also to find out the differences between the two projects. In this case, we use a set of rules as input data, and then apply these rules to specific projects or project groups that are similar or different from each other according to the rules. The result will be a list with some similarities and some differences. Frequent set mining is a key step of association rule mining. It determines the efficiency of association rule mining to a great extent. This paper first introduces the basic process of data mining, then introduces the association rule algorithm in E-commerce English, and focuses on how to use the improved association rule algorithm to mine the paths and page interests frequently visited by users in pattern recognition, which provides a basis for the personalized recommendation system model, This proves the application of the improved association rule algorithm in E-commerce English.

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Authors and Affiliations

  1. Guinlin College, Guangxi, 541004, China

    Xiaojia Lai

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  1. Xiaojia Lai
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Correspondence to Xiaojia Lai .

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Editors and Affiliations

  1. Department of Computer Science, Abdul Wali Khan University Mardan, Mardan, Pakistan

    Mian Ahmad Jan

  2. Department of Computer Science, Abdul Wali Khan University Mardan, Mardan, Pakistan

    Fazlullah Khan

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© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Lai, X. (2023). Application of Improved Association Rule Algorithm in E-commerce English. In: Jan, M.A., Khan, F. (eds) Application of Big Data, Blockchain, and Internet of Things for Education Informatization. BigIoT-EDU 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 466. Springer, Cham. https://doi.org/10.1007/978-3-031-23947-2_13

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  • DOI: https://doi.org/10.1007/978-3-031-23947-2_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23946-5

  • Online ISBN: 978-3-031-23947-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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