Abstract:
Courts require information technology that can handle the many ways that cases are
handled since not all cases are handled in the same way. As a result, AI can be helpful
for various sorts of court proceedings in various ways to decrease the case life cycle
and cases pendency at the courts. To make legal information both understandable,
actionable, and especially for providing right information at the right time, it has to
be organised and given meaning. The judgement data is made available to the pub lic for awareness and guidance. The massive volume of unstructured textual material
have made it challenging for AI systems to give consumers and their search queries the
best recommendations. Consequently, computing the similarity between numerical data
points is the most crucial component of those systems. AI may assist those seeking for
information, parties to a case, and judges with structured information. A system that
can retrieve similar cases will not only lessens human effort but also reduce the amount
of time it would take to retrieve similar cases. The study of machine learning and nat ural language processing (NLP) has advanced significantly since the widespread use of
the Internet. Therefore we have implemented a Siamese neural network and a Large Scale Multi-Label Text Classification having experiment with several neural classifiers
to compute the judgment similarity.
