基于认知属性库的原型范畴研究

李 斌;宋 丽;银思琪;曲维光;王 萌

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中文信息学报 ›› 2016, Vol. 30 ›› Issue (6) : 90-99.
综述

基于认知属性库的原型范畴研究

  • 李 斌1;宋 丽1;银思琪1;曲维光2;王 萌3
作者信息 +

A Prototype Theory Study Using Cognitive Property Bank

  • LI Bin1; SONG Li1; YIN Siqi1; QU Weiguang2; WANG Meng3
Author information +
History +

摘要

原型范畴是认知科学研究中的重要理论,使用属性来区分范畴中心成员及边缘成员有着较强的解释力,但该理论一直缺乏基于频率信息的属性数据支撑。该文借助认知属性库的23万条数据,对原型理论研究中经常讨论的“鸟”、“水果”、“交通工具”等范畴的典型成员和非典型成员进行分析验证。认知属性库的数据显示,在汉语中,“鸟”的典型成员是“麻雀”、“燕子”等,和“鸟”具有较多的共同属性;而“企鹅”、“鸵鸟”则只共享了“鸟”很少的属性,且缺少关键的属性“飞”。大体上验证了原型理论的观点。同时,我们也发现“小鸟”的属性特别丰富,具有典型成员的特性。在进一步观察了“水果”和“交通工具”两个范畴后,我们探讨了范畴的跨类现象,进而从数学模型上区分了树结构的层次分类体系和图结构的范畴化体系。

Abstract

As an important theory in cognitive science, the prototype theory is plausible to use properties to distinguish the central and periphery members in a category. However, there’s no quantitative evidence to support the theory. In this paper, we apply the cognitive property bank including 230,000 “word-property” pairs to validate the theory via 3 categories: bird, fruit and transportation. The results show that in Chinese, the typical members of bird are sparrow and swallow, which share many properties with bird. While the penguin and ostrich share very few properties with bird, especially lacking the key property fly. The data in cognitive property bank basically supports the idea of the prototype theory, but we also notice that the little bird has many properties, which make it available for a typical member in the category. We also distinguish between the tree based ontology and graph based categorization by bipartite graph.

关键词

认知属性 / 原型范畴 / 语义分类 / 语义计算

Key words

cognitive property / prototype theory / semantic categorization / semantic computation
 
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引用本文

导出引用
李 斌;宋 丽;银思琪;曲维光;王 萌. 基于认知属性库的原型范畴研究. 中文信息学报. 2016, 30(6): 90-99
LI Bin; SONG Li; YIN Siqi; QU Weiguang; WANG Meng. A Prototype Theory Study Using Cognitive Property Bank. Journal of Chinese Information Processing. 2016, 30(6): 90-99

参考文献

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基金

教育部青年基金(16YJC740034);山东省语言资源开发与应用重点实验室开放课题;江苏高校哲学社会科学研究项目(2016SJB740004);国家自然科学基金(61272221,61300152);国家科技支撑计划课题(2014BAK04B02)
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