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  • 标题:Transportation Service Quality Improvement through Closed Sequential Pattern Mining Approach
  • 本地全文:下载
  • 作者:Haisong Huang ; Liguo Yao ; Chieh-Yuan Tsai
  • 期刊名称:Cybernetics and Information Technologies
  • 印刷版ISSN:1311-9702
  • 电子版ISSN:1314-4081
  • 出版年度:2016
  • 卷号:16
  • 期号:3
  • 页码:185
  • DOI:10.1515/cait-2016-0042
  • 出版社:Bulgarian Academy of Science
  • 摘要:With the improvement of people's living quality, more attention has been paid in food safety and quality. This is especially true for perishable agricultural and dairy products. It is quite often that customers receive poor or broken products due to mistakes or wrong ways in transportation. This leads customers the unsatisfied for companies' products are relatively low. To solve the above problem, this paper proposes a new approach of using frequent closed sequential mining technology to analysis logistics data for helping companies to track the possible transportation problems. The approach consists of several important steps: RFID-enabled raw data collection, frequent sequential patterns mining, and patterns analysis. The experiment shows the proposed analysis method can discover many inside transportation service causes.
  • 关键词:Customer satisfaction; Transportation service; Data mining; Sequential ; patterns
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