Me-Based Chinese Person Name and Location Name Recognition Model

This paper constructs a hybrid model for automatic Chinese person name and location name recognition, which is based on maximum entropy principle. The model consists of a training module and a recognizing module. Firstly, contextual features are extracted from the training corpus. Maximum entropy principle is employed to train the features. Then, the trained features together with a dynamic word list and a simple rule base are used to recognize Chinese person names and location names in the testing corpus. The experimental results are satisfying and have been analyzed.