Performance in the Courtroom: Automated Processing and Visualization of Appeal Court Decisions in France
David RESTREPO AMARILES, Paul BONIOL, George PANAGOPOULOS, Christos XYPOLOPOULOS, Rajaa EL HAMDANI et Michalis VAZIRGIANNIS, « Performance in the Courtroom: Automated Processing and Visualization of Appeal Court Decisions in France », (2020) Proceedings of the Natural Legal Language Processing Workshop 2020 co-located with the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2020), en ligne : http://arxiv.org/abs/2006.06251.
Artificial Intelligence techniques are already popular and important in the legal domain. We extract legal indicators from judicial judgments to decrease the asymmetry of information of the legal system and the access-to-justice gap. We use NLP methods to extract interesting entities/data from judgments to construct networks of lawyers and judgments. We propose metrics to rank lawyers based on their experience, wins/loss ratio and their importance in the network of lawyers. We also perform community detection in the network of judgments and propose metrics to represent the difficulty of cases capitalising on communities features.
