Decision-Making Techniques and Methods for Sustainable Technological Innovation

14Classification of Indian Legal Judgment Documents Through Innovative Technology to Aid in Decision-Making

Ujjwal Pandey, Sukanya G. and Priyadarshini J.*

School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India

Abstract

Machine learning and deep learning techniques have revolutionized various fields such as art, science, math, and so on. However, these techniques have not been widely utilized in the legal domain, particularly in the Indian judiciary system, where most work is still done manually. In this study, we suggest a deep learning method for classifying the 18 categories established by the Supreme Court of India into which Indian court judgment documents fall. The approach outlined in this paper offers a more efficient way for legal professionals to classify and organize legal documents without the need for extensive manual review. Our approach uses a multichannel convolutional neural network (CNN) with multigram term frequency-inverse document frequency (TF-IDF) vectors as input and demonstrates superior performance compared to traditional machine learning and deep learning methods such as support vector machine, random forest, BERT, TextCNN, and so on in multilabel settings.

Keywords: Multilabel classification, machine learning, deep learning, Indian legal judgment documents, multichannel CNN, TF-IDF vectors

14.1 Introduction

In the Indian judicial system, a case presented by a plaintiff is divided into multiple categories enlisted ...