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A Text Mining Application in Operation Management Course Teaching

  • Yingying Qu
  • Zihang Liang
  • Wenxiu Xie
  • Xinyu CaoEmail author
Conference paper
  • 40 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11984)

Abstract

Sharing bicycle, as one of the hottest and newest industries in recent years, has drawn much dramatic attention from society. In the operation management course in this paper, students are expected to analyze the interview texts and investigate the problems occurred in sharing bicycle with corresponding suggestions. A list of interview texts from sharing bicycle users in Guangzhou Higher Education Mega Center are collected and analyzed. TF-IDF, as a widely used text mining method, is applied to extract frequently used key words for a qualitative analysis. Finally, ten key problems are identified and summarized, which provide government suggestions about supervision, such as user-centered management, user experience improvement, user interest protection, and deposit management.

Keywords

Text mining TF-IDF Content analysis Operation management course 

Notes

Acknowledgements

This paper is supported by the science and technology plan of Guangzhou (No. 201804010296) and Natural Science Foundation of Guangdong Province, China. (No. 2018A030310051).

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Yingying Qu
    • 1
  • Zihang Liang
    • 1
  • Wenxiu Xie
    • 2
  • Xinyu Cao
    • 3
    Email author
  1. 1.School of BusinessGuangdong University of Foreign StudiesGuangzhouChina
  2. 2.Department of Linguistics and TranslationCity University of Hong KongKowloonHong Kong SAR, China
  3. 3.China National Institute of StandardizationBeijingChina

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