An Affective-Similarity-Based Method for Somprehending Attributional Metaphors

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Author(s)

    • 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

Abstract

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.

Journal

  • Journal of Natural Language Processing

    Journal of Natural Language Processing 5(3), 3-31, 1998-07-10

    The Association for Natural Language Processing

References:  30

Cited by:  6

Codes

  • NII Article ID (NAID)
    10008827673
  • NII NACSIS-CAT ID (NCID)
    AN10472659
  • Text Lang
    ENG
  • Article Type
    Journal Article
  • ISSN
    13407619
  • Data Source
    CJP  CJPref  J-STAGE 
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