Generating Anthropomorphism of Subject and Verb by Transformation Matrix

Katsurou Takahashi, Hiroaki Ohshima, Kilho Shin
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Abstract

In this paper, given the subject-verb pairs, we propose a computational model to express the difference of the meaning of a verb when the subject has changed. We propose a method to generate metaphorical expressions consist of subject-verb pairs from the model. "Airship swims" is one of the example. It is the expression about the event that an airship flies in the sky gracefully. There are a few reasons why the expression is accepted for people. "airship flie" and the motion of a sea creature, for example "whale swims" represent both "the normal move in a space" and there is a similarity. Given the input ("airship," "fly"), we propose a method to detect a verb "swims" to generate metaphorical expressions considering these similarity. At first, we test which vectorization method is the best as the vectorization of a subject-verb pair. We calculate a transformation matrix to conserve between the meaning of (non-human subject, verb) pairs and the meaning of ("man", verb) pairs. We calcurate the transformation matrix between them using the stable meaning verbs as the anchors. In this paper, we test an hypothesis that we can use these transformation matrices to find an appropriate verb considering the difference of the meaning occured from the subjects. We gather 67 cases of target figurative expressions from Web. We evaluated the proposed method by defining the information retrieval problem of verbs.
用变换矩阵生成主谓拟人化
在本文中,我们提出了一个计算模型来表达当主语变化时动词意义的差异。我们提出了一种从模型中生成由主谓对组成的隐喻表达的方法。“飞艇游泳”就是一个例子。它是关于飞艇在天空中优雅地飞行的事件的表达。人们接受这种表达有几个原因。“飞艇飞行”和海洋生物的运动,例如“鲸鱼游泳”都代表了“空间中的正常运动”,并且有相似之处。给定输入(“飞艇”、“飞行”),我们提出了一种方法来检测动词“游泳”,以生成考虑这些相似性的隐喻表达。首先,我们测试了哪种向量化方法是最好的主谓对向量化方法。我们计算了一个变换矩阵来保存(非人类主语,动词)对和(“人”,动词)对的意义。我们以稳定意义动词为锚点,计算它们之间的变换矩阵。在本文中,我们检验了一个假设,即我们可以使用这些转换矩阵来找到一个合适的动词,考虑到从主语发生的意义的差异。我们从网络中收集了67例目标比喻表达。我们通过定义动词的信息检索问题来评估所提出的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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