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Mathematical Problems in Engineering
Volume 2014, Article ID 818203, 9 pages
http://dx.doi.org/10.1155/2014/818203
Research Article

Predicting Click-Through Rates of New Advertisements Based on the Bayesian Network

1Department of Computer Science and Engineering, School of Information Science and Engineering, Yunnan University, Kunming 650091, China
2Key Laboratory of Software Engineering of Yunnan Province, Kunming 650091, China
3Department of Software Engineering, School of Software, Yunnan University, Kunming 650091, China

Received 23 April 2014; Accepted 12 July 2014; Published 24 July 2014

Academic Editor: Guangming Xie

Copyright © 2014 Zhipeng Fang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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