Proceedings of the 2017 7th International Conference on Advanced Design and Manufacturing Engineering (ICADME 2017)

Method of Chinese data cleaning based on field matching algorithm and its application to freight quality management systems

Authors
Wenyang Tan, Xiushan Jiang, Shiyi Li
Corresponding Author
Wenyang Tan
Available Online July 2017.
DOI
10.2991/icadme-17.2017.15How to use a DOI?
Keywords
Data cleaning, data quality management
Abstract

Data cleaning, also called data cleansing or scrubbing, deals with detecting and removing errors and inconsistencies from data in order to improve the quality. Currently the problem is that people hold large amounts of data but do not get any useful knowledge, being described as "data rich but information poor". This paper will introduce data cleaning and study how to clean the Chinese data in a system based on the character matching algorithm and SNM method.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 7th International Conference on Advanced Design and Manufacturing Engineering (ICADME 2017)
Series
Advances in Engineering Research
Publication Date
July 2017
ISBN
10.2991/icadme-17.2017.15
ISSN
2352-5401
DOI
10.2991/icadme-17.2017.15How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Wenyang Tan
AU  - Xiushan Jiang
AU  - Shiyi Li
PY  - 2017/07
DA  - 2017/07
TI  - Method of Chinese data cleaning based on field matching algorithm and its application to freight quality management systems
BT  - Proceedings of the 2017 7th International Conference on Advanced Design and Manufacturing Engineering (ICADME 2017)
PB  - Atlantis Press
SP  - 82
EP  - 87
SN  - 2352-5401
UR  - https://doi.org/10.2991/icadme-17.2017.15
DO  - 10.2991/icadme-17.2017.15
ID  - Tan2017/07
ER  -