A Concise Review on Automatic Text Summarization

Abstract

Today, data is the most important thing humanity needs, thus understanding the linguistics of such a large data is not practically possible so, text summarization is introduced as the problem in natural language processing (NLP). Text summarization is the technique to convert long text corpus such that the semantics of the text does not change. This paper provides a study of different text summarization methods till Q3 2020. Text summarization methods are broadly classified as abstractive and extractive. In this paper, more focus is given to abstractive summarization a review for most of the methods of text summarization to date is written concisely along with the evaluations and advantages-disadvantages also for each method. At the end of the paper, the challenges faced by researchers for this task are mentioned and what improvements can be done in every method for summarization is also written in a structured way.