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The Scientific World Journal
Volume 2014, Article ID 468324, 11 pages
http://dx.doi.org/10.1155/2014/468324
Research Article

A Modified Decision Tree Algorithm Based on Genetic Algorithm for Mobile User Classification Problem

1College of Computer Science & Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China
2Center for Studies of Modern Business, Zhejiang Gongshang University, Hangzhou 310018, China

Received 31 October 2013; Accepted 23 December 2013; Published 9 February 2014

Academic Editors: T. Chen, Q. Cheng, and J. Yang

Copyright © 2014 Dong-sheng Liu and Shu-jiang Fan. 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.

Citations to this Article [6 citations]

The following is the list of published articles that have cited the current article.

  • Tarek Muhammad Noor, Danai Skoumetou, Gonzalo Seco-Granados, and Elena Simona Lohan, “User perception on Location Based Services: The more you know, the less you are willing to pay?,” Proceedings of 2014 International Conference on Localization and GNSS, ICL-GNSS 2014, 2014. View at Publisher · View at Google Scholar
  • Win-Tsung Lo, Yue-Shan Chang, Ruey-Kai Sheu, Chun-Chieh Chiu, and Shyan-Ming Yuan, “CUDT: A CUDA Based Decision Tree Algorithm,” The Scientific World Journal, vol. 2014, pp. 1–12, 2014. View at Publisher · View at Google Scholar
  • Bhanu Prakash Battula, Rama Krishna, and Tai-Hoon Kim, “An efficient approach for knowledge discovery in decision trees using inter quartile range transform,” International Journal of Control and Automation, vol. 8, no. 7, pp. 325–334, 2015. View at Publisher · View at Google Scholar
  • Bhanu Prakash Battula, Debnath Bhattacharyya, Prasad, and Tai-Hoon Kim, “A novel prototype decision tree method using sampling strategy,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9155, pp. 90–97, 2015. View at Publisher · View at Google Scholar
  • Yen-Liang Chen, Chia-Chi Wu, and Kwei Tang, “Time-constrained cost-sensitive decision tree induction,” Information Sciences, vol. 354, pp. 140–152, 2016. View at Publisher · View at Google Scholar
  • Yang Yu, Jiahao Wang, Chan Way Ng, Yukun Ma, Shupei Mo, Eliza Li Shan Fong, Jiangwa Xing, Ziwei Song, Yufei Xie, Ke Si, Aileen Wee, Roy E. Welsch, Peter T. C. So, and Hanry Yu, “Deep learning enables automated scoring of liver fibrosis stages,” Scientific Reports, vol. 8, no. 1, 2018. View at Publisher · View at Google Scholar