An Affective-Similarity-Based Method for Somprehending Attributional Metaphors

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著者

    • UTSUMI Akira
    • Tokyo Institute of Technology, Department of Computational Intelligence and Systems Science
    • HORI Koichi
    • The University of Tokyo, Interdisciplinary Course on Advanced Science and Technology
    • OHSUGA Setsuo
    • Waseda University, Department of Information and Computer Science

抄録

This paper proposes a new computational method for comprehending attributional metaphors. The proposed method generates deeper interpretations of metaphors than other methods through the process of figurative mapping that transfers affectively similar features of the source concept onto the target concept. Any features are placed on a common two-dimensional space revealed in the domain of psychology, and similarity of two features is calculated as a distance between them in the space. A computational model of metaphor comprehension based on the method has been implemented in a computer program called <I><B>PROMIME</B></I> (PROtotype system of Metaphor Interpreter with MEtaphorical mapping). Comparison between the <I><B>PROMIME</B></I> system's output and human interpretation shows that the performance of the proposed method is satisfactory.

収録刊行物

  • 自然言語処理 = Journal of natural language processing

    自然言語処理 = Journal of natural language processing 5(3), 3-31, 1998-07-10

    一般社団法人 言語処理学会

参考文献:  30件中 1-30件 を表示

被引用文献:  6件中 1-6件 を表示

各種コード

  • NII論文ID(NAID)
    10008827673
  • NII書誌ID(NCID)
    AN10472659
  • 本文言語コード
    ENG
  • 資料種別
    ART
  • ISSN
    13407619
  • データ提供元
    CJP書誌  CJP引用  J-STAGE 
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