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A Text Mining Application in Operation Management Course Teaching

  • Yingying Qu
  • , Zihang Liang
  • , Wenxiu Xie
  • , Xinyu Cao*
  • *Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

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.
Original languageEnglish
Title of host publicationEmerging Technologies for Education - 4th International Symposium, SETE 2019, held in Conjunction with ICWL 2019, Revised Selected Papers
EditorsElvira Popescu, Tianyong Hao, Ting-Chia Hsu
PublisherSpringer 
Pages257-266
ISBN (Electronic)9783030387785
ISBN (Print)9783030387778
DOIs
Publication statusPublished - Sept 2019
Event4th International Symposium on Emerging Technologies for Education (SETE 2019) - Magdeburg, Germany
Duration: 23 Sept 201925 Sept 2019

Publication series

NameLecture Notes in Computer Science
Volume11984
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Symposium on Emerging Technologies for Education (SETE 2019)
PlaceGermany
CityMagdeburg
Period23/09/1925/09/19

Research Keywords

  • Content analysis
  • Operation management course
  • Text mining
  • TF-IDF

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