Revision learning and its application to part-of-speech tagging

Authors:
Tetsuji Nakagawa;Taku Kudo;Yuji Matsumoto
Affiliations:
Nara Institute of Science and Technology, Takayama, Ikoma, Nara, Japan;Nara Institute of Science and Technology, Takayama, Ikoma, Nara, Japan;Nara Institute of Science and Technology, Takayama, Ikoma, Nara, Japan
Venue:
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Year:
2002

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Abstract

This paper presents a revision learning method that achieves high performance with small computational cost by combining a model with high generalization capacity and a model with small computational cost. This method uses a high capacity model to revise the output of a small cost model. We apply this method to English part-of-speech tagging and Japanese morphological analysis, and show that the method performs well.