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Analyzing the Quality of Business English Teaching Using Multimedia Data Mining

机译:用多媒体数据挖掘分析商务英语教学的质量

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Data continually act as a substantial role in business and industry for its daily activities to smoothly functional. The data volume is growing with the passage of time and rising of information technology. Using data mining techniques for quality evaluation and business English teaching is essential in the modern world. These technologies are introduced in the classroom, especially in online classes during the COVID-19 pandemic. To analyze the quality of business English teaching, this paper uses multimedia and data mining technologies. Initially, the multimedia data are collected during classes, and the association rule recommendation algorithm using data mining is applied. Based on collaborative filtering algorithms in association rules, indicators for teaching quality evaluation in colleges and universities are set up. Next, the actual teaching data of a university is used. Taking business English as an example, the algorithm that has been built is tested. The application of the algorithm is tested, and the teaching process of College Business English is evaluated. Finally, the conclusion is drawn that data mining technology can describe the behavior of teaching well and evaluate it, and it has the potential of popularization.
机译:数据在业务和行业中持续行动,为其日常活动顺利运作。数据量随着时间的推移和信息技术的上升而增长。利用数据挖掘技术进行质量评估和商务英语教学在现代世界中至关重要。这些技术在课堂上引入,特别是在Covid-19大流行期间的在线课程中。分析商务英语教学质量,本文采用多媒体和数据挖掘技术。最初,在类期间收集多媒体数据,并且应用了使用数据挖掘的关联规则推荐算法。基于关联规则中的协同过滤算法,建立了高校教学质量评估指标。接下来,使用大学的实际教学数据。以商务英语为例,测试已构建的算法。算法的应用经过测试,评估大学商务英语的教学过程。最后,得出的结论是,数据挖掘技术可以描述教学的行为并评估它,它具有普及潜力。

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  • 来源
    《Mobile information systems》 |2021年第a期|共8页
  • 作者

    Yanyan Xin;

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  • 入库时间 2022-08-19 02:20:23

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