The unstructured data impacts 95% of the organizations and costs them millions of dollars
annually. If managed well, it can significantly improve business productivity. The traditional …

Deep Learning has been widely used for tackling challenging natural language processing
tasks over the recent years. Similarly, the application of Deep Neural Networks in legal …

Natural language processing (NLP) based approaches have recently received attention for
legal systems of several countries. It is of interest to study the wide variety of legal systems …

The Amount of legal information that is being produced on a daily basis in the law courts is
increasing enormously and nowadays this information is available in electronic form also …

In this paper, we present our work on extracting and classifying requirements from large
software engineering contracts. Typically, the process of requirements elicitation begins after …

Legislation can be viewed as a body of prescriptive rules expressed in natural language.
The application of legislation to facts of a case we refer to as statutory reasoning, where …

The task of rhetorical role labeling is to assign labels (such as Fact, Argument, Final
Judgement, etc.) to sentences of a court case document. Rhetorical role labeling is an …

Recent years have witnessed an opportunity to improve trial efficiency and quality by
predictive analysis of massive judgment documents. A practical legal judgment prediction …

We consider the task of detecting contractual obligations and prohibitions. We show that a
self-attention mechanism improves the performance of a BILSTM classifier, the previous …

The daily transaction of an organization generates a vast amount of unstructured data such
as invoices and purchase orders. Managing and analyzing unstructured data is a costly …