Abstractive Text Summarization of Research Articles using RNN

Abstract

Abstractive summarization methods aims for producing important information using new way. In other words, they
use advanced natural language techniques to interpret and examine the text in order to generate a new shorter text that
conveys the most marginal information from the input text. This information overload increases in great demand for more
capable and dynamic text summarizers. There are a variety of applications like summaries of articles from newspaper,
textbook, educational magazine, anecdotes on the same topic, event, research paper, weather report, stock exchange, CV,
music, plays, film and speech. Hence it finds its importance. In this paper we discuss the use abstractive summarization for
research papers using RNN LSTM algorithm.