The Latent Dirichlet Allocation (LDA) generative model for automating process of rendering judicial decisions

Abstract

The Latent Dirichlet Allocation (LDA) generative model is widely used in statistical analysis and machine learning due to its ability to model the probabilities of multidimensional categorical data, such as the frequencies of different categories or the probability distribution across multiple categories. This article explores the potential application of the LDA model for the practical task of topic separation in documents related to judicial proceedings.