Items analysis of postal supervision

Yufen Cheng, Wenqian Shang, Ligu Zhu, Di Zhang, Dongyu Feng

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

1 Citation (Scopus)

Abstract

In the logistics industry, if every business know the flow and flow direction of different items and the type of items clearly, it will convenient for the business to make sales plan in time and improve the income. Based on the idea, this paper designs a method, which for carry out statistical analysis on the flow of items, and introduce the specific process. Face with the data which has large quantity, variety of item categories, the article design a program of data preprocessing at first, then calculate items' similarity by corpus-based approach, combined with the K-means cluster algorithm for the classification of items, and analysis of items' category. Analysis flow and flow direction by means of statistical analysis. At last, visualize the analysis result, output to foreground.

Original languageEnglish
Title of host publication2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings
EditorsKuniaki Uehara, Masahide Nakamura
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509008063
DOIs
Publication statusPublished - 23 Aug 2016
Externally publishedYes
Event15th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2016 - Okayama, Japan
Duration: 26 Jun 201629 Jun 2016

Publication series

Name2016 IEEE/ACIS 15th International Conference on Computer and Information Science, ICIS 2016 - Proceedings

Conference

Conference15th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2016
Country/TerritoryJapan
CityOkayama
Period26/06/1629/06/16

Keywords

  • K-means
  • classification
  • statistical analysis

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