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Modeling semantic similarity between metaphor terms of visual vs. linguistic metaphors through Flickr tag distributions

机译:通过Flickr标签分布对视觉隐喻术语与语言隐喻术语之间的语义相似性进行建模

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摘要

This study aims at modeling the semantic similarity between metaphor terms by means ofa distributional method based on a Big Data stream: Flickr tags. As explained in the article,this distributional model, Flickr Distributional Tagspace (FDT), captures primarily relationalsimilarity between concept pairs, that is, between tags that appear in similar tagsets(and therefore in similar pictures). A long established view in metaphor theory claims thatmetaphors pertain to the conceptual dimension of meaning, but while different modelsaim at explaining how language constructs and represents metaphorical conceptualstructures, we still know very little about how other modalities (for example, images)achieve metaphor construction and expression. A comprehensive theory, which argues infavor of the conceptual nature of metaphor, cannot afford to be biased toward the analysisand modeling of one specific modality of expression, thus neglecting potential modalityspecificdifferences. The present study, conducted through FDT, found that visual andlinguistic metaphors behave differently, in that the similarity between two aligned conceptsin a visual metaphor appears to be significantly higher than the similarity between twoconcepts aligned in a linguistic metaphor (which, in turn, does not differ substantiallyfrom the similarity between two randomly paired concepts). These findings suggest thatthe relational similarity between two metaphor terms (captured and modeled throughFDT) is crucial for visual metaphors but not for linguistic metaphors. An additional contentanalysis, also reported here, shows that the type of semantic information encoded in therelated tags (i.e., the contexts on which the contingency matrices of this distributionalmethod are built) differs, in relation to the modality of the metaphor: while situationrelatedand entity-related features are typically associated with concepts aligned in visualmetaphors, introspections, and taxonomic features are typically associated with conceptsaligned in linguistic metaphors.
机译:本研究旨在通过基于大数据流的Flickr标签分布方法,对隐喻术语之间的语义相似性进行建模。如文章所述,此分布模型Flickr分布标签空间(FDT)主要捕获概念对之间,即出现在相似标签集中(并因此出现在相似图片中的标签)之间的关系相似性。隐喻理论的一个长久以来的观点认为,隐喻与意义的概念维度有关,但是尽管不同的模型旨在解释语言是如何构建和表示隐喻概念结构的,但我们对其他模态(例如图像)如何实现隐喻构建以及表达。认为隐喻的概念性质不利的综合理论不能偏向于对一种特定表达方式的分析和建模,从而忽略了潜在的特定形式差异。通过FDT进行的本研究发现,视觉和语言隐喻的行为有所不同,因为视觉隐喻中两个对齐的概念之间的相似性似乎比语言隐喻中对齐的两个概念之间的相似性高得多(反过来,这两个概念之间没有相似性)。与两个随机配对的概念之间的相似性大不相同)。这些发现表明,两个隐喻术语(通过FDT捕获和建模)之间的关系相似性对于视觉隐喻至关重要,但对于语言隐喻却不重要。另外的内容分析(也报告在此)表明,与隐喻的形式有关,在相关标签(即,建立该分布方法的权变矩阵所基于的上下文)中编码的语义信息的类型有所不同:相关特征通常与在视觉隐喻,内省中对齐的概念相关联,而分类特征通常与在语言隐喻中对齐的概念相关联。

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    Bolognesi, M;

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