VICTOR: a Dataset for Brazilian Legal Documents Classification

This repo holds source code described in the paper below:

• Pedro H. Luz de Araujo, Teófilo E. de Campos, Fabricio Ataides Braz, Nilton Correia da Silva VICTOR: a Dataset for Brazilian Legal Documents Classification
  Language Resources and Evaluation Conference (LREC), May, Marseille, France, 2020.
  Download: [ paper | bib ]

We kindly request that users cite our paper in any publication that is generated as a result of the use of our code or our dataset.

Requirements

• Python 3
• pandas
• matplotlib
• scikit-learn
• XGBoost
• sklearn-crfsuite
• keras
• tensorflow

Files

• shallow_clf_docType.ipynb: notebook to train the shallow classifiers for document type prediction
• baseline_clf_themes.ipynb: notebook to train baseline classifiers for theme prediction
• dataset_statistics.ipynb: notebook to compute dataset statistics
• get_preds.py: script to compute and save model predictions (to use in the CRF experiments)
• crf_experiments.ipynb: notebook for CRF post-processing for document type classification
• train_cnn.py script to train CNN for document type classification
• train_lstm.py script to train LSTM for document type classification
• train_xgboost_themes.py script to train XGBoost for theme classification