A Survey on Text Summarization Techniques for Indian Legal Document Processing

Authors

  • Abhijeet Kumar Department Of Computer Science and Engineering, Sharda University Author
  • Sahil Kumar Department Of Computer Science and Engineering, Sharda University. Author
  • Kusum Lata Department Of Computer Science and Engineering, Sharda University. Author

Keywords:

Natural Language Processing (NLP), Text Summarization, Legal Document Summarization, Extractive Summarization, Abstractive Summarization, Legal NLP, Indian Judiciary.

Abstract

Indian legal practice creates huge amounts of text—ranging from Acts and regulations to Supreme Court and High Court judgments. Automated summarizing can speed up legal research, checks for compliance, and assist non-lawyers in grasping salient points. This survey goes over cutting-edge text summarization specific to Indian legal papers, addressing (1) extractive, abstractive, and hybrid approaches, (2) India-specific datasets and data acquisition methods; (3) India-specific challengesnacross domains (multilingualism, antiquated vocabulary, verbose judgments); (4) tools and frameworks; and (5) open issues and future research directions.

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Published

13-03-2026

Conference Proceedings Volume

Vol. 1(2026): Proceedings of IMPACT-2026

Section

Articles

License

Copyright (c) 2026 DMPedia Lecture Notes in Computer Science & Engineering

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Kumar, A. ., Kumar, S. ., & Lata, K. . (2026). A Survey on Text Summarization Techniques for Indian Legal Document Processing. DMPedia Lecture Notes in Computer Science & Engineering, IMPACT26, 108-117. https://digitalmanuscriptpedia.com/conferences/index.php/DMP-LNCSE/article/view/14