Summarizing News Paper Articles: Experiments with Ontology- Based, Customized, Extractive Text Summary and Word Scoring
Summarizing News Paper Articles: Experiments with Ontology- Based, Customized, Extractive Text Summary and Word Scoring
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新闻论文文章总结：基于本体的、定制的、抽取式文本摘要和单词评分的实验
DOI：
10.2478/cait-2012-0011
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发表时间：
2012
期刊：
影响因子：
4.3
通讯作者：
B. Eswara Reddy
中科院分区：
文献类型：
--
作者：
Jagadish S. Kallimani;K. Srinivasa;B. Eswara Reddy
摘要从海量文本中过滤信息的方法称为信息抽取。与理解全文相比，这是一项有限的任务。在全文理解中，我们以一种明确的方式表达给定文本中的所有信息。但是，在信息抽取中，我们提前划定，作为任务规范和结果语义范围的一部分。本研究仅考虑并发展了摘要摘要法。在本文中，通过考虑南印度地区语言之一(Kannada)，提出了一个使用新方法从大型文档中进行摘要的模型。它基于统计方法处理单个文档摘要。文章摘要的目的是为了便于快速准确地确定已发表文件的主题。这样做的目的是节省潜在读者的时间和精力，以便在一篇给定的大型文章中找到有用的信息。通过与英语语言的比较，讨论了对结果的各种分析。
Abstract The method for filtering information from large volumes of text is called Information Extraction. It is a limited task than understanding the full text. In full text understanding, we express in an explicit fashion about all the information in a given text. But, in Information Extraction, we delimit in advance, as part of the specification of the task and the semantic range of the result. Only extractive summarization method is considered and developed for the study. In this article a model for summarization from large documents using a novel approach has been proposed by considering one of the South Indian regional languages (Kannada). It deals with a single document summarization based on statistical approach. The purpose of summary of an article is to facilitate the quick and accurate identification of the topic of the published document. The objective is to save prospective readers’ time and effort in finding the useful information in a given huge article. Various analyses of results were also discussed by comparing it with the English language.