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© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM39095

Automated Legal Document Analysis Using Natural Language Processing

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM39095

Volume:

8 |

11 |

Nov 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM39095

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

RG

Rasik Gupta

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Abstract

Natural Language Processing (NLP) is now a valuable tool in legal document analysis and a cutting-edge tool in automating contract analysis, research, and compliance tracking. This paper aims to discuss the implementation of NLP in a field to analyze legal documents with emphasis placed on its effectiveness in increasing accuracy, efficiency, and access to the law profession. In this vein, selected NLP approaches, including Named Entity Recognition (NER), sentiment analysis, and text summarization, are made to address legal automation. Previous methods are considered and evaluated for applicability to large-scale legal texts to reveal the advantages and drawbacks of the available tools. Also, the paper outlines various developments of NLP technology that can be taken in a bid to enhance the legal automation process.

KEYWORDS

NLP Legal Analytics Legal AI NER Legal Text Analytics Summarization Legal AI Documenting Automation

Cite This Article

Rasik Gupta, "Automated Legal Document Analysis Using Natural Language Processing," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 11, Nov 2024. https://doi.org/10.55041/IJSREM39095

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Publication Date

11/23/2024

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The authors declare no conflict of interest related to this research work.

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