201. Information Extraction from Chinese Papers Based on Hidden Markov Model
- Author
-
Yan Zhang and Cheng Ying Chi
- Subjects
Markov chain ,Computer science ,business.industry ,Maximum-entropy Markov model ,Variable-order Markov model ,Speech recognition ,General Engineering ,Forward–backward algorithm ,Markov process ,Computer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing) ,Pattern recognition ,Markov model ,Viterbi algorithm ,symbols.namesake ,Computer Science::Sound ,symbols ,Markov property ,Forward algorithm ,Hidden semi-Markov model ,Artificial intelligence ,Hidden Markov model ,business - Abstract
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).
- Published
- 2013