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Indian Judgment Categorization for Practicing Similar Judgment Identification
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Author(s): Jenish Dhanani (Sardar Vallabhbhai National Institute of Technology, Surat, India), Rupa G. Mehta (Sardar Vallabhbhai National Institute of Technology, Surat, India), Dipti P. Rana (Sardar Vallabhbhai National Institute of Technology, Surat, India), Rahul Lad (Sardar Vallabhbhai National Institute of Technology, Surat, India), Amogh Agrawal (Sardar Vallabhbhai National Institute of Technology, Surat, India), Karan Chevli (Sardar Vallabhbhai National Institute of Technology, Surat, India)and Jashwanth Gummula Reddy (Sardar Vallabhbhai National Institute of Technology, Surat, India)
Copyright: 2021
Pages: 10
Source title:
Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance
Source Author(s)/Editor(s): Dipti P. Rana (Sardar Vallabhbhai National Institute of Technology, Surat, India)and Rupa G. Mehta (Sardar Vallabhbhai National Institute of Technology, Surat, India)
DOI: 10.4018/978-1-7998-7371-6.ch013
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Abstract
Recently, legal information retrieval has emerged as an essential practice for the legal fraternity. In the legal domain, judgment is a specific kind of legal document, which discusses case-related information and the verdict of a court case. In the common law system, the legal professionals exploit relevant judgments to prepare arguments. Hence, an automated system is a vital demand to identify similar judgments effectively. The judgments can be broadly categorized into civil and criminal cases, where judgments with similar case matters can have strong relevance compared to judgments with different case matters. In similar judgment identification, categorized judgments can significantly prune search space by restrictive search within a specific case category. So, this chapter provides a novel methodology that classifies Indian judgments in either of the case matter. Crucial challenges like imbalance and intrinsic characteristics of legal data are also highlighted specific to similarity analysis of Indian judgments, which can be a motivating aspect to the research community.
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