Supervised Machine Learning for summarizing Legal Documents

Mehdi Yousfi-Monod (yousfim <at> iro (point) umontreal (point) ca)

RALI, DIRO

Le 5 mai 2010 à 11 h 30

Salle 3195, Pavillon André-Aisenstadt


In my presentation I will describe a supervised machine learning approach for summarizing legal documents. A commercial system for the analysis and summarization of legal documents provided us with a corpus of almost 4,000 text and extract pairs for our machine learning experiments. We pre-processed that corpus to identify the selected source sentences in extracts from which we generated legal structured data. We then ran a sentence classification experiment relying on a Naive Bayes classifier using a set of surface, emphasis, and content features. Finally we compared our results against a baseline and the commercial system being used currently. [Ce séminaire est une "avant-première" d'une présentation à faire à Canadian AI 2010]


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