Proceedings of the 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control

Study and Application of Big Data Mining Based on Cloud Computing

Authors
Jie Shao
Corresponding Author
Jie Shao
Available Online April 2016.
DOI
10.2991/icmemtc-16.2016.8How to use a DOI?
Keywords
Cloud computing; Big data mining; Research and application
Abstract

With the constant improvement of Chinese economic development level, there have been constantly increasing researches on artificial intelligence and database field and the application of data mining in each field has been increasingly wide. However, with the increase of information quantity and data size, such information makes it more difficult to discover effective knowledge while helping the work and production of people. A lot of information is arranged in the specified equipment. However, mode and isomerism are more complicated and network noise increases. To process such data more effectively, cloud computing method can be used to handle problems that cannot be solved by traditional distributed computation method.

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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Volume Title
Proceedings of the 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control
Series
Advances in Engineering Research
Publication Date
April 2016
ISBN
978-94-6252-173-5
ISSN
2352-5401
DOI
10.2991/icmemtc-16.2016.8How 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  - Jie Shao
PY  - 2016/04
DA  - 2016/04
TI  - Study and Application of Big Data Mining Based on Cloud Computing
BT  - Proceedings of the 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control
PB  - Atlantis Press
SP  - 34
EP  - 38
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmemtc-16.2016.8
DO  - 10.2991/icmemtc-16.2016.8
ID  - Shao2016/04
ER  -