Automatic Text Summarization Using NLTK & Spacy
DOI:
https://doi.org/10.18486/ijcsnt/12.3.166Keywords:
NLTK, ATS, Abstractive, Extractive, SpacyAbstract
Automatic text summarization is a vital natural language processing task that aims to distill key information from large volumes of text. In this paper, we propose a technique of text summarization which focuses on the problem of identifying the most important portions of the text and producing coherent summaries which investigates the application of the Natural Language Toolkit (NLTK) in the context of text summarization. The study explores both extractive and abstractive summarization methods using NLTK & Spacy to generate concise summaries. The effectiveness of the NLTK-based and using Spacy library of python both summarization techniques is evaluated through experiments on input text. we have The research findings reveal the strengths and limitations of NLTK in text summarization and demonstrate its potential for facilitating efficient information extraction from textual data.
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Copyright (c) 2023 D M Akbar Hussain
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