PERSONAL NAME AND LOCATION NAME RECOGNITION BASED ON CONDITIONAL RANDOM FIELDS

A new approach was proposed to recognize personal name and location name based on conditional random fields in Chinese language domain. Some interesting features have been proposed, the new probabilistic feature is proposed, which are used instead of binary feature functions, however, it is one of the several differences between this model and the most of the previous CRFs-based model. We also explore several new features in our model, which includes local features, global features, hybrid feature, related features etc; Finally, the linguistics model with multi-knowledge is built. The proposed approach is evaluated with open test method using People's Daily (January, 1998), the evaluation results show that the F-measure is 85.91% for personal name and the F-measure is 93.14% for location name, which prove our approach has a good performance.