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A Survey on Text-Based Topic Summarization Techniques

A Survey on Text-Based Topic Summarization Techniques
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Author(s): T. Ramathulasi (Mother Theresa Institute of Engineering and Technology, Chittoor, India), U. Kumaran (Mother Theresa Institute of Engineering and Technology, Chittoor, India) and K. Lokesh (Mother Theresa Institute of Engineering and Technology, Chittoor, India)
Copyright: 2022
Pages: 13
Source title: Advanced Practical Approaches to Web Mining Techniques and Application
Source Author(s)/Editor(s): Ahmed J. Obaid (University of Kufa, Iraq), Zdzislaw Polkowski (Wroclaw University of Economics, Poland) and Bharat Bhushan (Sharda University, India)
DOI: 10.4018/978-1-7998-9426-1.ch001

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Abstract

The text summing method is obsolete due to recent advances in news articles, official documents, textual interpretation in scientific studies, manual text extraction, and many archives. Dealing with large amounts of text data requires the deployment of effective solutions. It is also impossible to capture text material due to high cost and labor. As a result, the academic community is increasingly interested in developing new ways to capture text automatically. Researchers have been working to improve the process of creating summaries since the invention of text summaries with the aim of creating machine summary matches with man-made summaries. Meaningful sentences are selected from the input document and added to the summaries using the hybrid technique. As a result, researchers are increasingly focusing on concise summaries to provide more coherent and relevant summaries. They use an artificial text summary to gather knowledge and information about recent research. A complete overview of abstraction methods is provided by a recent text summary created over the past decade.

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