论文信息 - Information Extraction from Chinese Papers Based on Hidden Markov Model

Information Extraction from Chinese Papers Based on Hidden Markov Model

Hidden Markov model HMM (1) is one of the important approaches for information extraction. In this paper, a model of the improved first-order hidden Markov HMM (2) is proposed. In the HMM (2), the output probability of the observation is not only dependent on the current state of the model, but also dependent on the previous state of the current state of the model. The algorithm of the ML and the algorithm of the Viterbi are analyzed. At last, experiments show that the HMM (2) is more precise than the HMM (1).

Yan Zhang | Cheng Ying Chi

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