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Erschienen in:
2006 | OriginalPaper | Buchkapitel
A Neural Network Model of Metaphor Understanding with Dynamic Interaction Based on a Statistical Language Analysis
verfasst von : Asuka Terai, Masanori Nakagawa
Erschienen in: Artificial Neural Networks – ICANN 2006
Verlag: Springer Berlin Heidelberg
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The purpose of this study is to construct a human-like neural network model that represents the process of metaphor understanding with dynamic interaction, based on data obtained from statistical language analysis. In this paper, the probabilistic relationships between concepts and their attribute values are first computed from the statistical analysis of language data. Secondly, a computational model of the metaphor understanding process is constructed, including dynamic interaction among attribute values. Finally, a psychological experiment is conducted to examine the psychological validity of the model.