Abstract
A court of a country is the main source of justice, to the respective country’s citizens. Every individual approaches courts to seek justice when his/her rights are violated. The main power house of these courts is the supreme court and each country has its own respective supreme court, in a country like India with a huge population every day hundreds and hundreds of new and appeal cases have been filed to the supreme court and seek justice. The objective of this paper is to classify the cases and to predict the behavior of the court (whether the appeal case will be accepted or dismissed by the Supreme Court). This paper gives the individual an ideology about how the case will be taken and treated by the court. The model considers past 20 years of cases from the Supreme Court of India database containing all types of cases to predict leave granted and Disposed off parameters. The proposed model is tested as three modules (i) classification module (ii) prediction module and (iii) baseline module and also compares various ML algorithms using Accuracy and F-measure as performance metrics.
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Sivaranjani, N., Jayabharathy, J. & Teja, P.C. Predicting the supreme court decision on appeal cases using hierarchical convolutional neural network. Int J Speech Technol 24, 643–650 (2021). https://doi.org/10.1007/s10772-021-09820-4
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DOI: https://doi.org/10.1007/s10772-021-09820-4