Document Summarization by Agglomerative nested clustering approach

Aakanksha Sharaff, Hari Shrawgi, Priyank Arora, Anshul Verma
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引用次数: 5

Abstract

Digital documents are ubiquitous in this age and every person faces an inundation of data today. In an era where being expeditious in work is becoming a necessity, providing people with the gist of verbose documents is an essential task. Thus in this paper, we document the process of Text Summarization in which a concise summary of a larger text is generated. We propose an Extractive Model of Document Summarization based on Agglomerative clustering which ranks sentences and forms a summary of the highly ranked sentences.
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基于凝聚嵌套聚类方法的文档摘要
数字文档在这个时代无处不在,今天每个人都面临着数据泛滥。在一个工作速度越来越快的时代,向人们提供冗长文件的要点是一项必不可少的任务。因此,在本文中,我们记录了文本摘要的过程,在这个过程中,一个更大的文本的简明摘要被生成。提出了一种基于凝聚聚类的文档摘要抽取模型,该模型对句子进行排序,并对排名较高的句子进行汇总。
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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