A multi-agent strategy for Chinese text chunking

Traditional Chinese text chunking approach is to identify phrases using only one model and same features. It is shown that one model couldn´t comprise each phrase´s characteristics, and same features are not suitable to all phrases, data sparseness also appears. Multi-agent strategy uses several model and sensitive features of each phrase to identify different phrases. This paper describes the multi-agent strategy applied in the identification of Chinese phrases whose main features are: 1) easy and quick communication between phrases; 2) avoidance of data sparseness. Through testing on Chinese Penn Treebank, F score of Chinese text chunking using multi-agent strategy achieves to 95.82%, which is higher than the best result that has been reported.