A Review on Automatic Text Summarization Techniques

  • Chaitanya Taru, Piyush Jadhav, Rasika Dhadphale and Pratik Shindekar


In today's era, there are a huge number of documents with humongous data in them. Going through all these documents is a time-consuming and tedious task. To make this a bit simple text summarization comes into the picture. Text summarization is obtaining a useful and short summary from a given input. Text summarization is classified into two types. Extractive summarization being the first one. In extractive summarization, the content of the summary is taken as it is from the given input. Abstractive summarization being the other option. Whereas in the abstractive summarization technique, contents of the summary are manipulated and new sentences are formed by the program from the given input. This output is created by Natural Language Processing (NLP). In this paper, various techniques of extractive text summarization are discussed.