Deep learning, a derived from machine learning, has grown into widespread usage with
applications as diverse as cancer detection, elephant spotting, and game development. The …

This paper describes VICTOR, a novel dataset built from Brazil's Supreme Court digitalized
legal documents, composed of more than 45 thousand appeals, which includes roughly 692 …

Like many other knowledge fields, the legal area has experienced an information-
overloaded scenario. However, to extract data from legal documents is a challenge due to …

We present and make available pre-trained language models (Phraser, Word2Vec,
Doc2Vec, FastText, and BERT) for the Brazilian legal language, a Python package with …

Studying and analyzing judicial documents are challenging tasks for the common person.
The basic reason for the complexity of documents is their long length with complex …

Word embeddings is a text representation technique capable of capturing syntactic and
semantic linguistic patterns and of representing each word as an n-dimensional dense …

In this era of information abundance, text segmentation can be used effectively to locate and
extract information specific to the user's needs, within a massive load of documents. Text …

O objetivo geral deste artigo é problematizar a utilização da Inteligência Artificial (IA) pelo
Supremo Tribunal Federal (STF) na identificação de repercussão geral em recurso …

The automatic text processing of natural language, with the use of probabilistic models and
neural networks allows the analysis and classification of large volumes of text, leading the …

Now days, the requirement for summarized and classified information has been increased
because, in this era of the internet, a lot of unstructured data is flowing rapidly. Legal …