认知语言学中对语篇认知复杂性的正式测量

Yingxu Wang, R. Berwick, Xiangfeng Luo, Jingsheng Lei
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引用次数: 6

摘要

自然语言文本的认知复杂性是衡量文本理解、处理和搜索过程中语法和语义特性的基本指标。本文提出了认知语言学中文本理解复杂性的形式化度量。本文对文本理解的客观和主观方面及其复杂性进行了形式化建模。建立了表征自然语言话语的形式语言模型。本文严格地描述了文本认知复杂性及其理解的数学模型。在认知语言学的认知模型和数学模型的基础上,定量地建立了语篇认知复杂性的测量方法,并通过一系列案例进行了检验。文本复杂性测量的广泛应用在认知语言学和当代网络技术中,如搜索引擎、在线文档检索、自然语言处理、认知语言学、认知计算、认知机器学习和单词计算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A formal measurement of the cognitive complexity of texts in cognitive linguistics
The cognitive complexity of texts in natural languages is a fundamental measure of the properties of syntax and semantics in textual comprehension, processing, and search. This paper presents a formal metrics of text comprehension complexity in cognitive linguistics. Both objective and subjective aspects of text comprehension and their complexity are formally modeled. A formal language model is established that characterizes the discourse of natural languages. The mathematical models of cognitive complexity of texts and their comprehension are rigorously described. On the basis of the cognitive and mathematical models of cognitive linguistics, the measurement of cognitive complexity of texts is quantitatively established and tested by a set of case studies. A wide range of applications of the measurement of textual complexity are identified in cognitive linguistics and contemporary web technologies such as search engines, online document retrieval, natural language processing, cognitive linguistics, cognitive computing, cognitive machine learning, and computing with words.
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