Word Relevance Computation for Noun-Noun Metaphor Recognition

摘要：

　　Metaphor in languages is an analogy-based meaning transfer phenomenon that impacts on question answering,machine translation and other tasks requiring deep semantic analysis.Noun-noun metaphor is a common type of metaphor and is studied in noun-noun semantic analysis.Lexical knowledge bases are important knowledge source for metaphor recognition and understanding.This paper proposes a method to compute word relevance for noun-noun metaphor recognition with the help of a lexical knowledge base,which shows good performance in the experiments.Furthermore,we investigate the representation of metaphor in lexical knowledge bases and its impact on the construction of lexical knowledge bases.

关键词： Metaphor Recognition Noun-noun Metaphor Word Relevance Lexical Knowledge.

作者: Yuxiang Jia Hongying Zan Ming Fan Shiwen Yu Zhimin Wang

作者单位: School of Information Engineering,Zhengzhou University,Zhengzhou,China Key Laboratory of Computational Linguistics,Peking University,MOE,Beijing,China College of Chinese Studies,Beijing Language and Culture University,Beijing,China

会议类型: 国际会议

会议名称: Chinese Lexical Semantics 15th Workshop(CLSW 2014)(第十五届汉语词汇语义学国际研讨会)

会议地点: 澳门

会议语种:英文

页码: 251-259

在线出版日期: 2014-06-09（万方平台首次上网日期，不代表论文的发表时间）