Analyzing Textual Documents Indexes by Applying Key-Phrases Extraction in Fuzzy Logic Domain Based on A Graphical Indexing Methodology

Latifa Rassam, Mohamed Raoui, A. Zellou, Moulay Hafid El Yazidi
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Abstract

Identifying and retrieving key phrases from a given corpus of textual documents is one of the fundamental problems of natural language processing, it is a vital subtask in the text summarization and comparison domain; through which we can obtain the most relevant set of phrases that approximately describe the content of a given document. In our manuscript, our principal objective will be introducing the approach of fuzzy-logic in the key phrase's indexing domain by proposing a new fuzzy logic-based methodology which evaluates the generated key phrases. We conduct a thorough empirical study of this methodology on a new textual document's corpus by identifying the degree of relevance of a key phrase linked to another one whether it is in the same corpus of textual documents or in two further fully distinct textual documents in the identical corpus.
基于图形索引方法的模糊逻辑域关键短语提取分析文本文档索引
从给定的文本文档语料库中识别和检索关键短语是自然语言处理的基本问题之一,是文本摘要与比较领域的重要子任务;通过它,我们可以获得最相关的一组短语,这些短语可以近似地描述给定文档的内容。在我们的手稿中,我们的主要目标是通过提出一种新的基于模糊逻辑的方法来评估生成的关键短语,从而将模糊逻辑方法引入关键短语的索引领域。我们对一个新的文本文档的语料库进行了彻底的实证研究,通过确定一个关键短语与另一个关键短语的关联程度,无论它是在同一文本文档的语料库中还是在同一语料库中的两个完全不同的文本文档中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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