A Qualitative Analysis for Predicting the Future of Auto Text Summarization in Natural Language Processing

This study conducts a qualitative analysis of the future prospects of auto summarization of text in Natural Language Processing. Auto-text summarization is one of the most discussed and well-known use cases of Natural Language Processing used to easily find the summary or conclusion of a lengthy text. Manually this process takes much more time but auto text-summarization reduces the time constraint by converting large text into a condensed form while maintaining its meaning and key information. This technique saves time and effort by focusing precisely on important points.In this paper, we also focused on the different types of text summarization and their uses, and a list of tools and methods available for text summarization. We are trying to predict the future of text summarization and the useful extensions needed in it to improvise the auto text-summarization process.