Information Extraction Algorithm Based on Multiple Templates Using Hidden Markov Model
Yunzhong Liu · Jisuanji gongcheng · 2006
This paper proposes a new algorithm using hidden Markov model for information extraction based on multiple templates due to the variety of training data. This new algorithm firstly clusters the training data into multiple templates based on the format, and then combines hidden Markov model for information extraction. The experiment results show that the new algorithm outperforms the original one, which hasn’t clustered the training data into multiple templates, in both recall and precision.