Over the past decades, the amount of information available on the Internet has increased exponentially. This creates the need to obtain valuable information or knowledge from a huge amount of data within a short period of time. The research community has conducted several natural language processing studies to improve automatic text summarization results. Several literature reviews in computational linguistics also aim to provide comprehensive knowledge about text summarization methods, approaches, and techniques. This survey article is distinguished because it provides a holistic review of studies on automatic text summarization advancements, challenges from 1953 to 2023, and future trends. As one of the new trends authors propose a predictive text summarization approach based on predictive analytics techniques. The results and conclusion contribute not only to the academic community, but also to cater to the interests of writers, journalists, and specialists in various fields which use summarization tools regularly.

Automatic text summarization(ATS) automatic text summarization approaches summarization systems predictive text summarization.