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A big data cleansing approach for n-dimensional RFID-Cuboids

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Radio Frequency Identification (RFID) technology has been widely used in manufacturing sites for supporting the shopfloor management. Huge amount of RFID-enabled production data has been generated. In order to discover invaluable information and knowledge from the RFID big data, it is necessary to cleanse such dataset since there is large number of noises. This paper uses n-dimensional RFID-Cuboids to establish the data warehouse. A big data cleansing approach is proposed to detect, remove and tidy the RFID-Cuboids so that the reliability and quality of dataset could be ensured before knowledge discovery. Experiments and discussions are carried out for validating the proposed approach. It is observed that the proposed big data cleansing approach outperforms other methods like statistics analysis in terms of finding incomplete and missing cuboids.

Original languageEnglish
Title of host publicationProceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2014
PublisherIEEE Computer Society
Pages289-294
Number of pages6
ISBN (Print)9781479937769
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event2014 18th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2014 - Hsinchu, Taiwan
Duration: 21 May 201423 May 2014

Publication series

NameProceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2014

Conference

Conference2014 18th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2014
Country/TerritoryTaiwan
CityHsinchu
Period21/05/1423/05/14

Keywords

  • big data
  • cuboid
  • data cleansing
  • n-dimensional
  • RFID

ASJC Scopus subject areas

  • Software

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