Abstract
In online communication, most of the time plain English characters are transmitted, while a few are encrypted. Thus there is a need for an automatic recognizer of plain English text (based on the characteristics of the English Language) without using a dictionary. It works for continuous text without word break-up (text without blank spaces between words). We propose a very efficient artificial neural network-based technique by selecting relevant or important features using Joint Mutual Information for online recognition of English plain text which can recognize English text from English like or random data.
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References
Saxena, P.K., Pratibha, Y.: Girish, M: Index of garbledness for automatic recognition of plain english texts. Defence Sci. J. 60(4), 415–419 (2010)
Yang, Howard Hua, Moody, John: Feature Selection based on Joint Mutual Information. J Comput Intell Methods Appl. Int. Comput. Sci. Convention 13, 1–8 (1999).
Haykin, S: Neural Networks- A Comprehensive Foundation, 2nd edn. Macmillan, New York.
Brown, Gavin, Pocock, Adam, Jhao, M.J., et al.: Conditional likelihood maximization: a unifying framework for information theoretic feature selection. J. Mach. Lear. Res. 13, 27–66 (2012).
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Bhateja, A., Bhateja, A., Din, M. (2014). Online Identification of English Plain Text Using Artificial Neural Network. In: Babu, B., et al. Proceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 2012. Advances in Intelligent Systems and Computing, vol 236. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1602-5_102
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DOI: https://doi.org/10.1007/978-81-322-1602-5_102
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