In the last years, the legal domain has been revolutionized by the use of Information and
Communication Technologies, producing large amount of digital information. 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 field of Natural Language Processing (NLP) has experienced significant growth in
recent years, largely due to advancements in Deep Learning technology and especially …

The surge in legal text production has amplified the workload for legal professionals, making
many tasks repetitive and time-consuming. Furthermore, the complexity and specialized …

Natural language processing (NLP) technologies and applications in legal text processing
are gaining momentum. Being one of the most prominent tasks in NLP, named-entity …

Predicting case outcomes is useful for legal professionals to understand case law, file a
lawsuit, raise a defense, or lodge appeals, for instance. However, it is very hard to predict …

Word embeddings have become important building blocks that are used profoundly in
natural language processing (NLP). Despite their several advantages, word embeddings …

Automated text categorization methods are of broad relevance for domain experts since they
free researchers and practitioners from manual labeling, save their resources (eg, time …

Transformer-based contextualized language models constitute the state-of-the-art in several
natural language processing (NLP) tasks and applications. Despite their utility …

In this paper, we present an entity-centric infrastructure to manage legal documents,
especially court judgments, based on the organization of a textual document repository and …