A Method of Calculating the Measure of Salience in Understanding Metaphors
A Method of Calculating the Measure of Salience in Understanding Metaphors
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一种计算理解隐喻显着性度量的方法
DOI：
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发表时间：
1990
期刊：
影响因子：
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通讯作者：
Hozumi Tanaka
中科院分区：
文献类型：
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作者：
Makoto Iwayama;T. Tokunaga;Hozumi Tanaka
本文提出了一种计算理解隐喻显着性度量的计算方法。我们主要以“A（像）B”的形式来对待隐喻，其中“A”称为目标概念，“B”称为源概念。在理解隐喻时，源概念的某些属性会转移到目标概念。在迁移过程中，我们首先要选择源概念中能够更好地迁移到目标概念的属性。显着性度量表示财产的典型性或突出程度，用于衡量财产的可转让性。通过引入显着性度量，我们只需考虑选择后的高显着性属性。显着性度量是根据Smith & Medin 的概率概念[12, 13]根据Tversky 的两个因子[14]计算出来的。一是强度，指的是信噪比；这是根据属性的熵计算的。另一个是诊断因素，指属性的分类意义；这是根据类似概念之间的属性强度分布计算得出的。最后，我们简要概述了使用显着性度量来理解隐喻的整个过程。
This paper presents a computaional method of calculating the measure of salience in understanding metaphors. We mainly treat metaphors in the form of "A is (like) B," in which "A" is called target concept, and "B" is called source concept. In understanding a metaphor, some properties of the source concept are transferred to the target concept. In the transfer process, we first have to select the properties of the source concept that can be more preferably transferred to the target concept. The measure of salience represents how typical or prominent the property is and is used to measure the transferability of the property. By introducing the measure of salience, we have to consider only the high salient properties after the selection. The measure of salience was calculated from Smith & Medin's probabilistic concept[12, 13] according to Tversky's two factors[14]. One is intensity which refers to signal-to-noise ratio; this is calculated from the entropy of properties. The other is diagnostic factor which refers to the classificatory significance of properties; this is calculated from the distribution of the property's intensity among similar concepts. Finally we briefly outline the whole process of understanding metaphors using the measure of salience.