  Predictive coding has been widely used in legal matters to find relevant or
privileged documents in large sets of electronically stored information. It
saves the time and cost significantly. Logistic Regression (LR) and Support
Vector Machines (SVM) are two popular machine learning algorithms used in
predictive coding. Recently, deep learning received a lot of attentions in many
industries. This paper reports our preliminary studies in using deep learning
in legal document review. Specifically, we conducted experiments to compare
deep learning results with results obtained using a SVM algorithm on the four
datasets of real legal matters. Our results showed that CNN performed better
with larger volume of training dataset and should be a fit method in the text
classification in legal industry.
