Proceedings of the 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)

Overview of Tourism Data Mining in Big Data Environment

Authors
Wenjie Xiao, Changguo Xiang
Corresponding Author
Wenjie Xiao
Available Online February 2017.
DOI
10.2991/emcm-16.2017.208How to use a DOI?
Keywords
Big data; Data mining; Cloud computing; Tourism; Clustering
Abstract

With the advent of the information age, the network is filled with all kinds of information and people in the vast amount of information are in the face of all kinds of confusion, thus data analysis has become a more difficult problem. Big data can solve this problem well and can greatly improve the efficiency of data mining. In order to apply the big data technology to the tourism industry, this paper introduces the concept of big data and the development demand of tourism big data, summarizes the common technology of data mining and the mining technology of tourism big data, and finally gives the application direction of data mining in tourism.

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 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)
Series
Advances in Computer Science Research
Publication Date
February 2017
ISBN
978-94-6252-297-8
ISSN
2352-538X
DOI
10.2991/emcm-16.2017.208How 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  - Wenjie Xiao
AU  - Changguo Xiang
PY  - 2017/02
DA  - 2017/02
TI  - Overview of Tourism Data Mining in Big Data Environment
BT  - Proceedings of the 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcm-16.2017.208
DO  - 10.2991/emcm-16.2017.208
ID  - Xiao2017/02
ER  -