Research of the Tourism Marketing Basing on the Data Mining

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With the development of economy, the tourism industry has become a pillar industry for national development. To speed up the development of the tourism industry, more rational capital investment for tourism, the reasonable layout of the facilities, make scientific decisions will be very important to tourism. Data mining technology has had a profound impact in many industries and areas. Among data mining association rules mining, because it can find a lot of interesting connections between data items, can provide the basis for our decision-making. Therefore, we will introduce data mining into tourism industry. Find out the hidden link in the tourism industry, in order to provide the basis for scientific decision-making.

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3659-3662

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March 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] J. Han, J. Pei, X.F. Yan. From Sequential Pattern Mining to Structured Pattern Mining: A Pattern-growth Approach. Journal of Computer Science and Technology, 2004, 19(3): 257-259.

DOI: 10.1007/bf02944897

Google Scholar

[2] Houtsma. M and Swami.A. Set-Oriented Mining for Association Rules in Relational Databases, Proceedings of the 11th IEEE International Conference on Data Engineering, Taipei, China, 1995: 25-34.

DOI: 10.1109/icde.1995.380413

Google Scholar

[3] R. Agrawal and R. Srikant Fast Algorithms for Mining Association Rules in Large Databases, Proceedings of the Twentieth International Conference on Very Large Databases Santiago, Chile, 1994: 487-499.

Google Scholar

[4] Gao Cong, Anthony K.H. Tung, Xin Xu, Fen Pan, Jiong Yang, FARMER: Finding Interesting Rule Groups in Microarray Datasets, In Proc of ACMSIGMOD, 2004: 143-154.

DOI: 10.1145/1007568.1007587

Google Scholar

[5] AGRAWALR, SRIKANT R. Fast Algorithms for Mining Association Rule [C]. Morgan Kaufmann, San Francisco, CA: Proceedings of the 24th International Conference on Very Large Databases, 1998: 478-499.

Google Scholar