  In this paper, we investigate the application of text classification methods
to support law professionals. We present several experiments applying machine
learning techniques to predict with high accuracy the ruling of the French
Supreme Court and the law area to which a case belongs to. We also investigate
the influence of the time period in which a ruling was made on the form of the
case description and the extent to which we need to mask information in a full
case ruling to automatically obtain training and test data that resembles case
descriptions. We developed a mean probability ensemble system combining the
output of multiple SVM classifiers. We report results of 98% average F1 score
in predicting a case ruling, 96% F1 score for predicting the law area of a
case, and 87.07% F1 score on estimating the date of a ruling.
