Information Retrieval Based Legal Search System

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Nilotpal Chatterjee
Inshal Khan
Mrigank Pagey
Anant Loiya
Avinash Agrawal
Ashwini Zadgaonkar

Abstract




Calculating the similarity between two legal documents to find similar legal judgments is an important challenge in legal information. Efficiently computing this similarity by expanding widely used information retrieval and search engine techniques has practical applications in a number of tasks, like locating pertinent prior cases for a specific case document. Programmed data recovery frameworks or reports are the main parts of today’s selected emotional support networks or web indexes to reduce data overload. Investigating methodologies to work on the presentation of report recovery frameworks and web search tools is a working area of research. Various methods have been pro- posed in this research paper to explore ways to search the common law system for cases with a similar outcome. Building a legal decision support system is intended to increase efficiency by assisting stakeholders—including judges and attorneys—in finding related rulings promptly. In order to prepare arguments, a lawyer typically has to review earlier decisions that are comparable to (or pertinent to) the current case. The attorney examines the judgement database to discover similar judgements. Legal rulings are complex in nature and refer to other judgments. For this, proper techniques are needed for quality analysis of judgments and correct deductions from them. A proper analysis of several types of similarity measures, such as all-term-based similarity methods, legal terms, co-citations, and bibliographic links, performed to look for comparable conclusions. According to experimental findings, the law term similarity approach outperforms all term cosine similarity methods. The out- comes also demonstrate that the co-citation approach performs worse than the bibliographic linkage similarity method and improves performance over the co-citation approach. After proper analysis of various methods in this field, proper comparison can be made between documents and similar legal documents can also be easily searched based on their similarity pattern and can be used to make meaningful deductions.




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Author Biographies

Nilotpal Chatterjee, Shri Ramdeobaba College of Engineering and Management, Nagpur

Nilotpal Chatterjee is a student of Shri Ramdeobaba College of Engineering and Management and is currently pursuing his bachelor’s degree in Computer Science and Engineering. His research interests include Deep Learning and Natural Language Processing.

Inshal Khan, Shri Ramdeobaba College of Engineering and Management, Nagpur

Inshal Khan is a student of Shri Ramdeobaba College of Engineering and Management and is currently pursuing his bachelor’s degree in Computer Science and Engineering. His research interests include Deep Learning and Natural Language Processing.

Mrigank Pagey, Shri Ramdeobaba College of Engineering and Management, Nagpur

Mrigank Pagey is a student of Shri Ramdeobaba College of Engineering and Management and is currently pursuing his bachelor’s degree in Computer Science and Engineering. His research interests include Deep Learning and Natural Language Processing.

Anant Loiya, Shri Ramdeobaba College of Engineering and Management, Nagpur

Anant Loiya is a student of Shri Ramdeobaba College of Engineering and Management and is currently pursuing his bachelor’s degree in Computer Science and Engineering. His research interests include Deep Learning and Natural Language Processing.

Avinash Agrawal, Shri Ramdeobaba College of Engineering and Management, Nagpur

Dr. Avinash J. Agrawal Dr. Avinash J. Agrawal is the Head of Department in CSE at Shri Ramdeobaba College of Engineering and Management, Nagpur. He has completed his graduation B.E. (Computer Technology) in 1998 from Nagpur University and M.Tech. (Computer Technology) from National Institute of Technology, Raipur in the year 2005. His subjects of specialization include Information Retrieval, NLP, Pattern Recognition Compiling for High Performance Architecture, Language Processors and Artificial Intel- ligence

Ashwini Zadgaonkar, Shri Ramdeobaba College of Engineering and Management, Nagpur

Ashwini Zadgaonkar Ashwini Zadgaonar is an Assistant Professor in the Dept. of CSE at RCOEM, Nagpur. She has graduated from B.Tech Computer Technology and M.tech in CSE from Nagpur University and currently pursuing her Phd at RCOEM,RTMNU Nagpur. Her subject specialization include Artificial Intelligence, Natural Language Pro- gramming , Software Engineering

How to Cite
Chatterjee, N., Khan, I. ., Pagey, M. ., Loiya, A. ., Agrawal, A., & Zadgaonkar, A. . (2023). Information Retrieval Based Legal Search System. International Journal of Next-Generation Computing, 14(1). https://doi.org/10.47164/ijngc.v14i1.1004

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