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Journal of Applied Mathematics
Volume 2014, Article ID 675806, 7 pages
Research Article

Decision Tree Classification Model for Popularity Forecast of Chinese Colleges

Department of Computer Science, Xiamen University, Xiamen, Fujian 361005, China

Received 25 December 2013; Accepted 5 April 2014; Published 24 April 2014

Academic Editor: Jose L. Gracia

Copyright © 2014 Xiangxiang Zeng 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.


Prospective students generally select their preferred college on the basis of popularity. Thus, this study uses survey data to build decision tree models for forecasting the popularity of a number of Chinese colleges in each district. We first extract a feature called “popularity change ratio” from existing data and then use a simplified but efficient algorithm based on “gain ratio” for decision tree construction. The final model is evaluated using common evaluation methods. This research is the first of its type in the educational field and represents a novel use of decision tree models with time series attributes for forecasting the popularity of Chinese colleges. Experimental analyses demonstrated encouraging results, proving the practical viability of the approach.