乌尔都语文本反摘要智能系统

Muhammad Wasif Bhatti, Muhammad Aslam
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引用次数: 2

摘要

文本去摘要是一种增加文档内容并解释文本要点的方法。对于人类来说,从大型文章中手动解释中心主题是一项非常粗糙的任务。反摘要可以分为抽象方法和提取方法两个分支。摘要将原文件中的祈使句或段落累积起来,作为解释呈现出来。乌尔都语从阿拉伯语、波斯语和南亚本土语言中继承了大量词汇。由于这种影响,乌尔都语有一个复杂的形态学。在语法方面,它有一个相对自由的词序(主语、宾语和动词)。尽管有数百万人使用乌尔都语,但就可用的计算资源而言,乌尔都语是一种资源不足的语言。我们扩展了基于句子权重算法的乌尔都语单文档提取反摘要方法,特别是针对新闻、体育、健康等主题。我们通过预处理(句子分割、标记化、停止词和词序化)对稿件进行封装,并应用句子权重算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ISUTD: Intelligent System for Urdu Text De-Summarization
Text De-Summarization is a method of increasing the document and explains the substantial point of the text. It is very rough assignment for humans to manually explain the central subject from the large article. De- Summarization can be separating into two branches as Abstractive and Extractive approaches. Extractive accumulates the imperative paragraph or sentence from the original document and presents them as an explanation. Urdu inherits a lot of vocabulary from Arabic, Persian and the native languages of South Asia. Due to this effect, Urdu has a complex morphology. In terms of syntax, it has a relatively free word order (Subject, Object, and Verb). Despite spoken by millions of people, Urdu is an under-resourced language in terms of available computational resources. We extent the single document extractive de-summarization methodology for Urdu based on the sentence weight algorithm especially for the news, sports, and health etc. topics. We encapsulate the manuscript by preprocessing (sentence segmentation, tokenization, stop words and lemmatization) and apply sentence weight algorithm.
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