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An analysis of the relationship between cohesion and clause combination in English discourse employing NLP and data mining approaches

机译:基于NLP和数据挖掘方法的英语语篇中衔接与从句组合的关系分析

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摘要

This study examines the relationship between the frequencies of clause combination and the distribution of discourse-pragmatic markers of cohesion in a sub-sample of the Susanne corpus. It addresses the theory that clause grammar constitutes a form of grammar-cued discourse coherence which functions as an integrated system with other methods of managing coherence in language. Evidence is sought for whether increased clause density in a corpus correlates with a reduction in explicit cohesive devices. To address this, a computational approach is outlined for the coding of cohesion in a corpus, using a semi-automated data mining procedure. To validate this approach, it is compared with cohesion measures on the same data using the NLP tool Coh-Metrix 3.0. The two approaches are shown to positively correlate on a series of measures, suggesting they significantly overlap in quantifying the cohesion construct. The final analysis of the tagged corpus indicates that as frequencies of clause combination increase in a text, the use of explicit lexical cohesive devices decrease. Also, higher frequencies of clause combination positively correlate with an increased use of grammatical cohesive devices. Findings are interpreted as generally aligning with the expectations of the theoretical framework known as the Adaptive Approach to Grammar.
机译:本研究考察了从句组合频率与Susanne语料库子样本中话语-语用语凝聚力标记分布之间的关系。它解决了从句语法构成一种语法提示话语连贯性的理论,它与其他管理语言连贯性的方法一起作为一个集成系统发挥作用。寻找证据来证明语料库中子句密度的增加是否与显性内聚装置的减少相关。为了解决这个问题,概述了一种计算方法,用于使用半自动数据挖掘程序在语料库中编码内聚力。为了验证这种方法,它与使用 NLP 工具 Coh-Metrix 3.0 对相同数据的内聚度量进行了比较。这两种方法在一系列措施上显示出正相关,表明它们在量化凝聚力结构方面显着重叠。对标记语料库的最终分析表明,随着文本中从句组合频率的增加,显式词汇内聚装置的使用减少。此外,从句组合频率越高,语法内聚手段的使用增加也呈正相关。研究结果被解释为与被称为语法适应性方法的理论框架的期望基本一致。

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