UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Volume 11 | Issue 10 | October 2024

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Volume 10 Issue 11
November-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2311388


Registration ID:
528440

Page Number

d724-d727

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Title

TEXT SUMMARIZATION USING NATURAL LANGUAGE PROCESSING AND MACHINE LEARNING

Abstract

This proposed system focuses on the development and implementation of a sophisticated text summarization system using Natural Language Processing (NLP) and Machine Learning, specifically leveraging the Latent Semantic Analysis (LSA) algorithm. Text summarization is a critical aspect of information retrieval and comprehension, enabling users to grasp the essence of large volumes of text quickly and efficiently. Despite the advancements in NLP and ML, there remains a gap in the implementation of a comprehensive summarization system that incorporates LSA. Our project aims to bridge this gap by designing and deploying a novel system that harnesses the power of LSA to extract latent semantic relationships within textual data, thereby generating concise and meaningful summaries. The proposed system will not only enhance the efficiency of information processing but also contribute to the existing body of knowledge in the field of text summarization. Through the integration of LSA, the project seeks to capture the underlying semantic structure of documents, allowing for a more nuanced and contextually relevant summarization. As we embark on the implementation phase, the objective is to address the current absence of a fully realized LSA-based summarization system, providing a valuable tool for researchers, businesses, and individuals dealing with vast amounts of textual information. This project is poised to make a significant contribution to the advancement of text summarization techniques, highlighting the potential of LSA within the broader landscape of NLP and ML applications.

Key Words

Summarization, Natural Language Processing (NLP), Machine Learning (ML), Latent Semantic Analysis (LSA), Information Retrieval, Textual Data, Implementation.

Cite This Article

"TEXT SUMMARIZATION USING NATURAL LANGUAGE PROCESSING AND MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 11, page no.d724-d727, November-2023, Available :http://www.jetir.org/papers/JETIR2311388.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"TEXT SUMMARIZATION USING NATURAL LANGUAGE PROCESSING AND MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 11, page no. ppd724-d727, November-2023, Available at : http://www.jetir.org/papers/JETIR2311388.pdf

Publication Details

Published Paper ID: JETIR2311388
Registration ID: 528440
Published In: Volume 10 | Issue 11 | Year November-2023
DOI (Digital Object Identifier):
Page No: d724-d727
Country: Nashik, Maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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