An Artificial Intelligence based Analysis in Legal domain

Abstract

Around the world, legitimate information and common laws are available in raw form, but hard to understand and not in organized form. All legitimate information is nowadays computerized since the legal information gets generated on a regular basis in a huge volume due to increase of maritime (law) courts. The automation tool to analyse this legal data can serve effectively for lawyers and law students, which can address a lawyer’s role and can even become powerful to release such a role in future. The machine learning and deep learning algorithmsbased analysis systems apply these methods mainly for document classification. Legal document translation, text classification, summarization, data forecasting and data obtainment are part of the goals got from research charity. In this study, we review about the different methods of deep learning used in legal tasks such as Legal data search, Legal document analytics, and Legal perspective interface. To solve aggregate tasks, one can use the deep learning methods like, Recurrent Network Networks (RNN), Gated Recurrent unit network (GRU), Long Short Term Memory networks (LSTM), Convolutional neural network (CNN). Through this review, we instituted that deep learning models are giving advanced performance