Automatic text summarization and it's methods - a review

Neelima Bhatia, Arunima Jaiswal
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引用次数: 20

Abstract

Text summarization is an incipient practice for verdict out the summary of the text article. Text summarization has grew so uses such as Due to the enormous aggregate of information getting augmented on internet; it is challenging for the user to verve through altogether the information accessible on web. The large availability of internet content partakes constrained a broad research area in the extent of automatic text summarization contained by the Natural Language Processing (NLP), especially statistical machine learning communal. Terminated the bygone half a century, the defaulting has been addressed from numerous diverse standpoints, in erratic domains and using innumerable archetypes. In this survey paper we investigate the popular and important work done in the field of single and multiple document summarizations, generous distinctive prominence towards pragmatic approaches and extractive techniques. Particular auspicious slants that quintessence on unambiguous minutiae of the summarization are also deliberated. Exceptional consideration is ardent to involuntary assessment of summarization classifications, as forthcoming investigation on summarization is sturdily reliant over evolvement in this problem space.
自动文本摘要及其方法综述
摘要是对文本文章的摘要进行判定的一种初步实践。文本摘要的使用越来越多,例如由于互联网上大量的信息被增强;对于用户来说,浏览网络上所有可访问的信息是一项挑战。网络内容的大量可用性限制了自然语言处理(NLP),特别是统计机器学习领域对自动文本摘要的研究。在过去的半个世纪里,违约已经从许多不同的角度,在不稳定的领域和使用无数的原型来解决。在这篇调查论文中,我们调查了在单一和多个文件摘要领域所做的流行和重要的工作,对实用主义方法和提取技术的慷慨突出。特别吉祥的倾向,国粹对明确的细节总结也深思熟虑。特别的考虑是热心于对摘要分类的非自愿评估,因为即将进行的对摘要的调查非常依赖于这个问题空间的演变。
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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