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A computational model of lexical cohesion analysis and its application to the evaluation of text coherence.

机译:词汇衔接分析的计算模型及其在文本衔接性评估中的应用。

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摘要

In this thesis, we discuss how to apply the analysis of lexical cohesion in texts to the problem of evaluating text coherence. We have two objectives. The first one is to create a computational model to represent the lexical cohesion of a given text. In order to store this information we design a new data structure--the lexical graph--with lexical items as nodes and lexical relations between those items, such as synonymy, represented as arcs. This structure is particularly suitable for short texts. For longer texts, we propose a different but related data structure, the collapsed lexical graph, with paragraphs as nodes and lexical bonds as arcs.; Next, we show how to apply our model for the representation of cohesion to the problem of evaluating text coherence, for texts of arbitrary length. We present hypotheses on how to detect the sites of possible coherence problems based on the cohesion information supplied by our model. We also describe an experiment which we conducted to confirm the validity of our model, comparing the predictions of the model with text evaluations performed by human judges.; In addition, we discuss the areas of application for the model, commenting on how detecting sites of possible incoherence can be of value to problems such as text critiquing and second language learning and proposing new improvements to automated procedures such as natural language generation and machine translation.; The thesis therefore provides important new research within the field of computational linguistics on how a representation of the cohesion of a text provides an understanding of the coherence of that text.
机译:在本文中,我们讨论了如何将文本中的词汇衔接分析应用于评估文本连贯性的问题。我们有两个目标。第一个是创建一个计算模型来表示给定文本的词汇衔接。为了存储此信息,我们设计了一个新的数据结构-词汇图-以词汇项作为节点,而这些项之间的词汇关系(例如同义词)表示为弧。此结构特别适合于短文本。对于较长的文本,我们提出了一个不同但相关的数据结构,即折叠词图,其中段落为节点,词法键为弧。接下来,我们将展示如何将我们的内聚表示模型应用于评估文本连贯性(对于任意长度的文本)的问题。我们提出了关于如何根据我们的模型提供的内聚信息来检测可能存在相干问题的站点的假设。我们还描述了一个为确认模型有效性而进行的实验,将模型的预测结果与人工判断的文本评估结果进行了比较。此外,我们讨论了该模型的应用领域,评论了如何检测可能存在不连贯性的站点如何对诸如文本批评和第二语言学习之类的问题有价值,并提出了对自动程序的新改进,例如自然语言生成和机器翻译。;因此,本论文在计算语言学领域提供了重要的新研究,涉及文本衔接的表示如何提供对文本衔接的理解。

著录项

  • 作者

    Makuta, Marzena Halina.;

  • 作者单位

    University of Waterloo (Canada).;

  • 授予单位 University of Waterloo (Canada).;
  • 学科 Computer Science.; Language Linguistics.
  • 学位 Ph.D.
  • 年度 1998
  • 页码 243 p.
  • 总页数 243
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;语言学;
  • 关键词

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