一种基于条件随机场的人名识别方法

Identification of Person Name Based on Conditional Random Fields

本文提出了一种基于统计的中文人名识别方法，此方法使用最大概率分词模型对源句子进行粗切分，将粗切分信息融入到条件随机场模型中进行模型的训练。运用此方法分别对来自同一源语料的测试集和非同源语料的测试集进行了测试，F-值分别达到了91．3％和90．6％，证明了此方法的有效性。

This paper presents a probabilistic approach of person name recognition. First coarsely segment the text and then add the segment tags to conditional random fields model. The approach is tested on two testing sets： one comes from the same copra as the training set and the other is not, and the F-score reaches 91.3% and 90.6% respectively. The result proves the validity of this approach.