Title: Text Information Extraction Based on Clustering Hidden Markov Model
Abstract: Using Hidden Markov model is an important approach for text information extraction.The form is dissimilar for texts which are from different resource of network.The optimal model is commonly difficult to obtain by hybrid training texts.Clustering was applied to text information extraction.Clustering was given to Markov Chains of training texts through an improved approach of K-mean,and Hidden Markov model was trained out through every cluster.An algorithm of text information extraction based on clustering hidden Markov model(C-HMM) was proposed.A simulation experiment of information extraction was tried on 700 texts from different resource of network.Results show that the performance of extraction can be improved effectively by using the new algorithm.
Publication Year: 2007
Publication Date: 2007-01-01
Language: en
Type: article
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Cited By Count: 3
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