Cognitive Studies: Bulletin of the Japanese Cognitive Science Society
Online ISSN : 1881-5995
Print ISSN : 1341-7924
ISSN-L : 1341-7924
Feature: Rethinking Concept Research
A Computational Model of Metaphor Understanding based on a Probabilistic Concept Structure -Using Statistical Analysis of Japanese Corpus-
Asuka TeraiMasanori Nakagawa
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2010 Volume 17 Issue 1 Pages 129-142

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Abstract

The purpose of this study to clarify the cognitive process associated with comprehension of metaphorical expression “B is like A” using model simulations and psychological experiments. The process of understanding the metaphor in the form of “B is like A” is regarded as the process that transforms the meaning of the target “B” into the meaning of the metaphor. In our model, nouns are represented probabilistically by meaning vectors based on the concept structure estimated using statistical analysis of Japanese corpus. This model assumes that metaphor understanding consists of two processes. The first is the categorization process; according to Class Inclusion Model (Glucksberg \& Kayser, 1990), a target is assigned to an ad hoc category of which the vehicle is a prototypical member. The second is the dynamic interaction process; the target assigned to the ad hoc category is influenced by dynamic interaction among features. Feature emergence occurs through this dynamic interaction. In order to verify the psychological validity of our model, we first conducted psychological experiments followed simulation studies based on the experiments. The results showed that our model that incorporates both categorization and dynamic interaction processes performed better than a model with only categorization process in prediction human cognitive behaviors, providing evidence for its psychological validity.

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© 2010 Japanese Cognitive Science Society
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