Chinese noun phrase metaphor recognition with maximum entropy approach

Authors:
Zhimin Wang;Houfeng Wang;Huiming Duan;Shuang Han;Shiwen Yu
Affiliations:
Department of Computer Science and Technology, Institute of Computational Linguistics, Peking University, Beijing, China;Department of Computer Science and Technology, Institute of Computational Linguistics, Peking University, Beijing, China;Department of Computer Science and Technology, Institute of Computational Linguistics, Peking University, Beijing, China;Department of Computer Science and Technology, Institute of Computational Linguistics, Peking University, Beijing, China;Department of Computer Science and Technology, Institute of Computational Linguistics, Peking University, Beijing, China
Venue:
CICLing'06 Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing
Year:
2006

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Abstract

This paper presents a maximum entropy (ME)-based model for Chinese noun phrase metaphor recognition. The metaphor recognizing process will be viewed as a classification task between metaphor and literal meaning. Our experiments show that the metaphor recognizer based on the ME method is significantly better than the Example-based methods within the same context windows. In addition, performance is further improved by introducing additional features into the ME model and achieves good results in window (-2,+2).