Leiden University Centre for Linguistics, Universiteit Leiden.
Institut für Sprache und Information, Heinrich-Heine-Universität Düsseldorf.
Cogn Sci. 2021 Sep;45(9):e13029. doi: 10.1111/cogs.13029.
Cognitive scientists have long used distributional semantic representations of categories. The predominant approach uses distributional representations of category-denoting nouns, such as "city" for the category city. We propose a novel scheme that represents categories as prototypes over representations of names of its members, such as "Barcelona," "Mumbai," and "Wuhan" for the category city. This name-based representation empirically outperforms the noun-based representation on two experiments (modeling human judgments of category relatedness and predicting category membership) with particular improvements for ambiguous nouns. We discuss the model complexity of both classes of models and argue that the name-based model has superior explanatory potential with regard to concept acquisition.
认知科学家长期以来一直使用类别分布语义表示。主要方法是使用表示类别名称的名词的分布表示，例如“city”表示城市类别。我们提出了一种新的方案，即用成员名称的表示来表示类别原型，例如“Barcelona”、“Mumbai”和“Wuhan”表示城市类别。在两项实验（对类别相关性的人类判断建模和预测类别成员）中，基于名称的表示在经验上优于基于名词的表示，对于模糊名词尤其有改进。我们讨论了这两类模型的模型复杂度，并认为基于名称的模型在概念获取方面具有更好的解释潜力。
