METAPHOR RECOGNITION: CHMETA, A PATTERN-BASED SYSTEM

被引:3
作者
Yang, Yun [1 ]
Zhou, Changle [1 ,2 ]
Ding, Xiaojun [1 ,3 ]
Chen, Jiawei [1 ]
Shi, Xiaodong [1 ]
机构
[1] Xiamen Univ, Inst Artificial Intelligence, Xiamen, Peoples R China
[2] Zhejiang Univ, Ctr Study Language & Cognit, Hangzhou 310003, Zhejiang, Peoples R China
[3] Xiamen Univ, Coll Foreign Languages & Cultures, Xiamen, Peoples R China
关键词
natural language processing; pattern recognition; metaphor recognition; metaphor role dependency schema; referential unconventionality; collocational unconventionality; CHMeta;
D O I
10.1111/j.1467-8640.2009.00349.x
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Metaphor recognition presents a computational challenge, in part due to metaphoric deviation from literal thinking, and also because of a metaphor's various linguistic expressions. This article forwards a new computational method, an integrated treatment of metaphor recognition from the computational perspective, which recent related studies have not entirely addressed. The authors differentiate metaphor recognition from complex metaphor inference and interpretation employing psychological clues. To accomplish this, we have developed a formalized system of metaphorical expression in metaphor role dependency schema, which specifically defines, classifies, and quantifies metaphorical anomalies, building a computable classification system formetaphors (incorporating 32 major patterns of metaphorical expressions) by providing a strategy to locate potential metaphorical anomalies in a target input sentence through a pattern recognition method and a metaphor components' tagging approach. This metaphor recognition and tagging system is named and implemented as "CHMeta." Experiment results support the validity and efficiency of this metaphor recognition system. Compared with most metaphor computation systems, which work mainly on a few examples, this system classifies major metaphorical expressions from a computational perspective and is able to recognize a variety of different kinds of metaphors, including nested ones. Thus, this is the first integrated work in computable classification, recognition, and tagging of large-scale metaphors in Chinese.
引用
收藏
页码:265 / 301
页数:37
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