Title: Text Information Extraction Based on the Second-Order Hidden Markov Model
Abstract: Hidden Markov model is one of important approaches for text information extraction.In the first-order hidden Markov model,there is the hypothesis that the transition probability of state and the output probability of observation are only depen- dent on the current state of the model,which debases the precision of information extraction comparatively.The relationship between the probability and the model's historical states is considered reasonably in the second-order hidden Markov model which has stronger performance of recognition for incorrect information.An algorithm of text information extraction based on the second-order hidden Markov model is proposed.The validity of the second-order hidden Markov model in information extraction is analyzed. Simulation Experiments show that the new algorithm has higher precision than the algorithm based on the first-order hidden Markov model.
Publication Year: 2007
Publication Date: 2007-01-01
Language: en
Type: article
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Cited By Count: 3
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