Abstract
In this paper, we propose a method which finds salient features automatically in a metaphorical expression consisting of two noun concepts. First, we prepared a bundle of features by human association experiments on the concepts, and, using the bundle, we implemented SD (Semantic Differential) Method experiments to evaluate the features. Then, we extracted common salient features by using a new neural network mechanism where the result of the SD Method experiments were used for the parameters of the mechanism. Since this mechanism can be applied to any pair of concepts to form a sentence “T is V”, saliency of features which are common to the T and V is evaluated quantitatively. We show examples calculated by the system to verify its effectiveness.
