Research Paper Summarization using Extractive summarizer

The rapid growth of scientific literature in various domains has made it increasingly challenging for researchers to stay updated with the latest developments in their fields. This paper explores the application of Natural Language Processing techniques to address the issue by automatically generati...

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Bibliographic Details
Published in:	2024 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS) pp. 1 - 6
Main Authors:	Zunke, Sonali, Shrivastava, Alka, Sakhare, Komal, Bhatkar, Ajay, Prajapati, Atul, Sheikh, Mahawish, Yedke, Mansi
Format:	Conference Proceeding
Language:	English
Published:	IEEE 24-02-2024
Subjects:	BERT Summarizer Cleaning Computer science Data mining Electric potential Extractive Summarization Flask Flutter Name Entity Recognition (NER) Printing Text recognition TF-IDF Vectorizer
Online Access:	Get full text
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Summary:	The rapid growth of scientific literature in various domains has made it increasingly challenging for researchers to stay updated with the latest developments in their fields. This paper explores the application of Natural Language Processing techniques to address the issue by automatically generating concise and coherent summaries of research papers. The script goes through multiple steps, including text extraction, cleaning, applying NLP processes, combining TF-IDF and BERT summaries, removing names of people using Named Entity Recognition (NER), removing repeated words, and finally, trimming the summary to a desired word limit before printing it. The purpose is to generate an accurate and meaningful summary of the document content.
ISSN:	2688-0288
DOI:	10.1109/SCEECS61402.2024.10481994