Dynamically Weighted Hidden Markov Model for Spam Deobfuscation

Abstract

Spam deobfuscation is a processing to detect obfuscated words appeared in spam emails and to convert them back to the original words for correct recognition. Lexicon tree hidden Markov model (LTHMM) was recently shown to be useful in spam deobfuscation. However, LT-HMM suffers from a huge number of states, which is not desirable for practical applications… (More)

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Cite this paper

@inproceedings{Lee2007DynamicallyWH, title={Dynamically Weighted Hidden Markov Model for Spam Deobfuscation}, author={Seunghak Lee and Iryoung Jeong and Seungjin Choi}, booktitle={IJCAI}, year={2007} }