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Metaphor recognition using automatic classification of adjectives based on statistical method

机译:基于统计方法使用形容词的自动分类来识别

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摘要

In this paper, we propose a method of metaphor recognition using automatic classification of adjectives based on statistical approach. We have defined adjective vector and calculated similarity between adjectives. An adjective vector is described by frequency of nouns which modify the adjectives. Masui et. al. have introduced two probabilistic measurements: "salience gap" and "novelty" which are based on conceptual description of metaphorical words. In the conceptual description, properties of words, which are adjectives, are classified into several categories using similarity between adjectives. We have extracted metaphorical expressions from newspaper corpus and classified into exemplify, metaphor and others by 20 human examiners. Using this test sets, we have conducted experiments of metaphor recognition and the results was almost 80 percent accuracy.
机译:在本文中,我们提出了一种基于统计方法的形容词自动分类来提出一种隐喻识别方法。 我们已经确定了形容词矢量并计算形容词之间的相似性。 通过修改形容词的名词频率描述形容词矢量。 Masui et。 al。 介绍了两个概率测量:“显着差距”和“新奇”,其基于隐喻词的概念描述。 在概念描述中,单词的属性是形容词的分类为使用形容词之间的相似性的若干类别。 我们已经从报纸语料库中提取了隐喻表达,并将其分类为20人审查员的举例说明,隐喻等。 使用此测试集,我们对隐喻识别进行了实验,结果差不多了80%。

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