A neural network model of metaphor understanding with dynamic interaction based on a statistical language analysis

Authors:
Asuka Terai;Masanori Nakagawa
Affiliations:
Tokyo Institute of Technology, Tokyo, Japan;Tokyo Institute of Technology, Tokyo, Japan
Venue:
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Year:
2006

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Abstract

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.