A Multi-agent Model for English Text Chunking

Author

Liang, Ying-Hong ; Li, Jin-xiang ; Cao, Jun ; Wang, De-peng

Author_Institution

JiangSu Province Support Software Eng. R&D Center for Modern Inf. Technol. Applic. in Enterprise, Suzhou, China

Volume

1

fYear

2009

Firstpage

88

Lastpage

92

Abstract

Traditional English text chunking approach is to identify phrases using only one model and same features. It is shown that one model could not consider each phrasepsilas characteristics, and same features are not suitable to all phrases. In this paper, a multi-agent text chunking model is proposed. This model uses individual sensitive features of each phrase to identify different phrases. Through testing on the public training and test corpus, this multi-agent model is effective because F score of English chunking using this multi-agent model achieves to 95.70%, which is higher than the best result that has been reported.

Keywords

grammars; learning (artificial intelligence); multi-agent systems; natural language processing; text analysis; English text chunking approach; machine learning; multiagent model; natural language processing; phrase characteristics; shallow parsing; Application software; Computer science; Data mining; Information technology; Learning systems; Natural language processing; Research and development; Software engineering; Testing; Text processing; Multi-agent; Text Chunking; sensitive features;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Technology and Computer Science, 2009. ITCS 2009. International Conference on

Print_ISBN

978-0-7695-3688-0

Type

conf

DOI

10.1109/ITCS.2009.26

Filename

5190023