Chunk Parsing with Maximum Entropy Principle
Li Su · Chinese Journal of Computers · 2003
This paper proposes to use Maximum Entropy (ME) model to conduct Chinese chunk parsing. First we define Chinese chunks and list all chunk categories and tags used in the model. Thus the process of chunking can be regarded as a classification problem which trains from the corpus with chunk tags and POS tags. The focus of ME model is how to select useful features. Then, the procedure and algorithms of feature selection is introduced. At last we test the model, and experimental results are given.