Abstract-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.
Wei et al. REF used a Convolution Neural Network (CNN) to implement text classification for legal document review, and their experimental results show that the CNN model performs much better than SVM with a larger volume training dataset.
Empirical Study of Deep Learning for Text Classification in Legal Document Review
ArXiv
ArXiv
Computer Science