Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)

Application of Data Mining Technology in Tourism Information Recommendation

Authors
Wanchun Zhu
Corresponding Author
Wanchun Zhu
Available Online May 2017.
DOI
10.2991/msmee-17.2017.20How to use a DOI?
Keywords
Data mining; Tourism; Information recommendation; Application
Abstract

With the continuous improvement of the economy, the tourism industry has gradually become a trend, rich attractions, service diversification has been loved by the majority of tourists. However, with the rapid development of tourism, it is also faced with many difficulties. It is very important to carry out the recommendation according to the characteristics of tourists' preferences and tourist information. It is difficult for tourists to make a choice of tourist attractions and ways in the absence of reliable information. Data mining is a process of decision support, is the deep data analysis method, this paper uses the Apriori algorithm to recommend tourism information for data mining, analysis according to the personal preferences of tourists, to help visitors make a choice. Effectively improve the accuracy of recommendation.

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 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)
Series
Advances in Engineering Research
Publication Date
May 2017
ISBN
978-94-6252-346-3
ISSN
2352-5401
DOI
10.2991/msmee-17.2017.20How 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  - Wanchun Zhu
PY  - 2017/05
DA  - 2017/05
TI  - Application of Data Mining Technology in Tourism Information Recommendation
BT  - Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)
PB  - Atlantis Press
SP  - 93
EP  - 98
SN  - 2352-5401
UR  - https://doi.org/10.2991/msmee-17.2017.20
DO  - 10.2991/msmee-17.2017.20
ID  - Zhu2017/05
ER  -