Text information extraction is an important approach to processing large quantity of text.Maximum entropy provides a kind of framework for natural language processing.A new algorithm using hidden Markov model based on maximal entropy is proposed for text information extraction.The new algorithm combines the advantage of maximum entropy model

which can integrate and process rules and knowledge efficiently

with that of hidden Markov model

which has powerful technique foundations to solve sequence representation and statistical problem

and uses the sum of all features with weights to adjust the transition parameters in hidden Markov model for text information extraction.Experimental results show that the new algorithm improves the performance in precision and recall.