Extractive

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• Published Subscription Review Article 8 Feb 2025

  Exploring Technologies for Extractive Text Summarization: A Review of Transformer and Reinforcement Learning Models

  By Rajshree Tarapure, Sharayu Mulay, Ashlesha Kathe, Prapti Jadhav, Shalaka Deore

  Abstract: In recent years, the size of information on the Internet has increased exponentially. Therefore, a solution is needed to transform large amounts of raw data into useful information the human brain can understand. Automatic Text Summarization (ATS) is a part of Natural Language Processing (NLP) that aims to take long texts and shorten them, keeping the most important information in a clear and easy-to-understand way. This research report explores methods …

  Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 1–6 Read article →