Maximum Entropy Markov Models for Information Extraction and Segmentation

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1.The use of state-observation transition functions rather than the separate transition and observation functions in HMMs allows us to model transitions in terms of multiple, nonindependent features of observations, which we believe to be the most valuable contribution of the present work.

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Maximum Entropy Markov Models for Information Extraction and Segmentation

标签：os   io   for   cti   ar   res   rac   c   

原文地址：http://www.cnblogs.com/kevinGaoblog/p/3881525.html