Proceedings of the 2016 International Conference on Economics and Management Innovations

Scientific research of early warning under the "Big Data"

Authors
A mu-la A mu-la, Guo-bo Zhuang
Corresponding Author
A mu-la A mu-la
Available Online July 2016.
DOI
10.2991/icemi-16.2016.15How to use a DOI?
Keywords
Big data, early warning mechanism of corrupion, Scientific anti-corruption, Path exploration
Abstract

With the rapid development of information technology, the informationization tide impact on all aspects of human society. Under the background of big data, reasonable use of the growing data resources, to establish a set of scientific basis for the early warning mechanism, in order to speed up the anti-corruption "upgrade", the most timely and scientific early warning of corruption, is to implement the current anti-corruption "in treating symptoms, to win the time" the path to the root of the problem is to maintain the health of the body of the party and the government inevitable choice.

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/).

Download article (PDF)

Volume Title
Proceedings of the 2016 International Conference on Economics and Management Innovations
Series
Advances in Computer Science Research
Publication Date
July 2016
ISBN
10.2991/icemi-16.2016.15
ISSN
2352-538X
DOI
10.2991/icemi-16.2016.15How to use a DOI?
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/).

Cite this article

TY  - CONF
AU  - A mu-la A mu-la
AU  - Guo-bo Zhuang
PY  - 2016/07
DA  - 2016/07
TI  - Scientific research of early warning under the "Big Data"
BT  - Proceedings of the 2016 International Conference on Economics and Management Innovations
PB  - Atlantis Press
SP  - 75
EP  - 80
SN  - 2352-538X
UR  - https://doi.org/10.2991/icemi-16.2016.15
DO  - 10.2991/icemi-16.2016.15
ID  - Amu-la2016/07
ER  -