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.

中文翻译：

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使用多媒体数据挖掘分析商务英语教学质量

数据在日常活动中的正常运行一直在企业和行业中扮演着重要角色。随着时间的流逝和信息技术的发展，数据量在不断增长。在现代世界中，使用数据挖掘技术进行质量评估和商务英语教学至关重要。这些技术是在教室中引入的，尤其是在COVID-19大流行期间的在线课堂中。为了分析商务英语教学的质量，本文使用了多媒体和数据挖掘技术。最初，在上课期间收集多媒体数据，并应用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，建立了大学教学质量评价指标。下一个，使用大学的实际教学数据。以商务英语为例，对已构建的算法进行测试。测试了该算法的应用，评估了大学商务英语的教学过程。最后得出结论，数据挖掘技术可以很好地描述和评价教学行为，具有推广的潜力。