文章基本信息

标题：Relevant Content Extraction and Text Summarization
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作者：Yashashvi Sharma ; Ashutosh Dixit
期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2017
卷号：8
期号：2
页码：170-173
语种：English
出版社：Ayushmaan Technologies
摘要：Text Summarization is a process of extracting or collecting important information from original text and providing that information in the form of summary. It is an important research area in today’s era of the fast growing information age. As information is growing day by day on the internet, it is difficult for users to identify the relevant information. Users have to read the whole document to determine whether the given document is relevant or not. With the help of text summarization a shorter version of large text documents by keeping relevant information from the original text document can be generated. In this work, the focus is on the comparison of clustering technique and novelty detection technique used in generating summary of the documents.
关键词：Text Summarization;Clustering;Extractive Summarization; Abstractive Summarization;Vector Space Model