Outlier Detection and Processing Technology and Its Application

DOI

10.2991/icmcm-16.2016.5How to use a DOI?

Keywords

Outlier detection;Data cleaning;Attribute anomalies;Duplicatedrecords.

Abstract

Faced with the development of information technology and the arrival of the era of big data, data has become the advanced productive forces and strategic resources. However, the existence of outliers often has a negative impact on the storageand analysis of the data, andeven causes disastrous consequences. This paper starts with the definition, concept and classification of outliers, and then compares and analyzes various methods of outlier detection and cleaning technology based on attribute anomaly and the duplicate or similarrecords.Finally, the research and application of outliers are prospected.

Copyright

© 2016, 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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TY  - CONF
AU  - Yong Wang
AU  - Jiahe Cui
AU  - Zebao Zhang
AU  - Zhigang Li
PY  - 2016/12
DA  - 2016/12
TI  - Outlier Detection and Processing Technology and Its Application
BT  - Proceedings of the 2016 7th International Conference on Mechatronics, Control and Materials (ICMCM 2016)
PB  - Atlantis Press
SP  - 18
EP  - 24
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmcm-16.2016.5
DO  - 10.2991/icmcm-16.2016.5
ID  - Wang2016/12
ER  -