• Maitry Desai
• Jatayu Baxi

With significant amount of textual information getting generated every day, text summarization has become essential part of any text analytic tool. Instead of having to go through the entire text, it is convenient to understand the essence of the text by its summary which covers important information from the original document. Summary of the text can be either extractive or abstractive based on the content of summary. This paper focuses more on extractive text summarization. In this paper we first give introduction of the text summarization problem and challenges associated with it. We focus on related work done in the field of extractive text summarization and prepare list of features which can be used to generate summary of the document. We analyze some of the popular techniques to build extractive text summarizer and their trade off. We also discuss recently used deep learning technique for text summarization. We discuss methods to evaluate accuracy of the automatically generated summary and discuss some popular applications where text summarization can be effectively used

Text summarization, Extractive summarization, Abstractive text summarizations

"A Survey on Various Techniques to build Extractive Text Summarizer", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.495-500, December-2018, Available :http://www.jetir.org/papers/JETIR1812970.pdf

"A Survey on Various Techniques to build Extractive Text Summarizer", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp495-500, December-2018, Available at : http://www.jetir.org/papers/JETIR1812970.pdf