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The Scientific World Journal
Volume 2014 (2014), Article ID 625342, 17 pages
http://dx.doi.org/10.1155/2014/625342
Research Article

Improved Feature-Selection Method Considering the Imbalance Problem in Text Categorization

College of Information Engineering, Northeast Dianli University, Jilin, Jilin 132012, China

Received 13 February 2014; Revised 18 April 2014; Accepted 23 April 2014; Published 26 May 2014

Academic Editor: Yudong Cai

Copyright © 2014 Jieming Yang 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.

Citations to this Article [7 citations]

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

  • Alper Kursat Uysal, “An improved global feature selection scheme for text classification,” Expert Systems with Applications, 2015. View at Publisher · View at Google Scholar
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  • Deniz Kılınç, Akın Özçift, Fatma Bozyigit, Pelin Yıldırım, Fatih Yücalar, and Emin Borandag, “TTC-3600: A new benchmark dataset for Turkish text categorization,” Journal of Information Science, vol. 43, no. 2, pp. 174–185, 2017. View at Publisher · View at Google Scholar
  • Mohamed Nadjib Meadi, Mohamed Chaouki Babahenini, and Abdelmalik Taleb Ahmed, “New use of the HITS algorithm for fast web page classification,” Turkish Journal of Electrical Engineering and Computer Sciences, vol. 25, no. 3, pp. 2015–2032, 2017. View at Publisher · View at Google Scholar
  • D. Muthusankar, B. Kalaavathi, and P. Kaladevi, “High performance feature selection algorithms using filter method for cloud-based recommendation system,” Cluster Computing, 2018. View at Publisher · View at Google Scholar