Text Summarization Using NLP

Abstract

This paper provides a detailed view of how the development and usage of a natural language processing text summarizer have occurred. Based on its requirement to present condensed yet meaningful conclusions without affecting the original meaning of the given data, this system is built up. Techniques utilized, like feature extraction, preprocessing of the given data, and summarization itself, have also been mentioned within this research paper. It also reviews how well the system performs in benchmark datasets, and it expounds on some of its applications, limitations, and possible further developments. In this study, it shows quite well how hard-core NLP algorithms can treat the challenges encountered in modern text summarization