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The Scientific World Journal
Volume 2013, Article ID 950796, 7 pages
http://dx.doi.org/10.1155/2013/950796
Research Article

A Kernel-Based Approach for Biomedical Named Entity Recognition

Department of Computer Science & Engineering, Birla Institute of Technology, Mesra, Ranchi 835215, India

Received 31 August 2013; Accepted 30 September 2013

Academic Editors: Y. Muto and J. Yu

Copyright © 2013 Rakesh Patra and Sujan Kumar Saha. 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.

  • Jim Jing-Yan Wang, and Xin Gao, “Minimum Information Loss Based Multi-kernel Learning for Flagellar Protein Recognition in Trypanosoma Brucei,” 2014 IEEE International Conference on Data Mining Workshop, pp. 133–141, . View at Publisher · View at Google Scholar
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  • Sindhuja Gopalan, and Sobha Lalitha Devi, “BNEMiner: Mining biomedical literature for extraction of biological target, disease and chemical entities,” International Journal of Business Intelligence and Data Mining, vol. 11, no. 2, pp. 190–204, 2016. View at Publisher · View at Google Scholar