Abstract
The peer-reviewed articles and textual data are main source of data in biology. Text mining is solution to extract information from textual data sources that are usually in bulky quantities, messy and disorganized. Dealing with this situation needs to deploy innovative methods and techniques. In this paper, we identify the current heavily used methods for biomedical text mining, their capabilities and developments, some proposed solution and how to evaluate performance. Biomedical specific challenges in text mining context have been studied with respect to proposed answers and then main future trends based on current needs and requirements have been discussed. © 2012 IEEE.
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CITATION STYLE
Faiiazee, H., Al-Haddad, S. A. R., Abdullah, R., & Samsudin, K. (2012). Text mining in bioinformatics: Past, present and future. In Proceedings - 2012 International Conference on Information Retrieval and Knowledge Management, CAMP’12 (pp. 327–330). https://doi.org/10.1109/InfRKM.2012.6205000
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