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Title: Automatic Text Summarization Tool
Authors: Chauhan, Shivangi
Aswani, Reema [Guided by]
Keywords: Summarization systems
Extractive summaries
Machine learning
Issue Date: 2015
Publisher: Jaypee University of Information Technology, Solan, H.P.
Abstract: Today‘s world is all about information, most of it online. The World Wide Web contains billions of documents and is growing at an exponential pace. Tools that provide timely access to, and digest of, various sources are necessary in order to alleviate the information overload people are facing. These concerns have sparked interest in the development of automatic summarization systems. Such systems are designed to take a single article, a cluster of news articles, a broadcast news show, or an email thread as input, and produce a concise and fluent summary of the most important information. Recent years have seen the development of numerous summarization applications for news, email threads, lay and professional medical information, scientific articles, spontaneous dialogues, voicemail, broadcast news and video, and meeting recordings. These systems, imperfect as they are, have already been shown to help users and to enhance other automatic applications and interfaces.
Appears in Collections:B.Tech. Project Reports

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