Proceedings of the 2nd International Conference on Soft Computing in Information Communication Technology

Application and Empirical Research of Data Mining Technology in Decision Optimization of Chinese Publishing Enterprise

Authors
Shuo Liu
Corresponding Author
Shuo Liu
Available Online May 2014.
DOI
10.2991/scict-14.2014.40How to use a DOI?
Keywords
data mining; OLAP; association analysis; decision support
Abstract

As the age of big data is coming and the market is becoming increasingly competitive, it’s important for enterprise to discover the knowledge and rules existing in big data for decision optimization. Publishing schedule and association of publications have become two important factors which must be considered during the publishing decision making process. This paper firstly analyzes the feasibility of data mining used in Chinese publishing industry. Then, a scientific decision making process based on data mining is established. Finally, we collect a mass of book sales data to show the practical application of data mining in publishing decision support.

Copyright
© 2014, 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 2nd International Conference on Soft Computing in Information Communication Technology
Series
Advances in Intelligent Systems Research
Publication Date
May 2014
ISBN
10.2991/scict-14.2014.40
ISSN
1951-6851
DOI
10.2991/scict-14.2014.40How to use a DOI?
Copyright
© 2014, 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  - Shuo Liu
PY  - 2014/05
DA  - 2014/05
TI  - Application and Empirical Research of Data Mining Technology in Decision Optimization of Chinese Publishing Enterprise
BT  - Proceedings of the 2nd International Conference on Soft Computing in Information Communication Technology
PB  - Atlantis Press
SP  - 168
EP  - 171
SN  - 1951-6851
UR  - https://doi.org/10.2991/scict-14.2014.40
DO  - 10.2991/scict-14.2014.40
ID  - Liu2014/05
ER  -