36 citations · 90 across the 6 of their papers we have counts for
6 papers
CNN Application in Detection of Privileged Documents in Legal Document Review
Rishi Chhatwal, Robert Keeling, Peter Gronvall +3
Protecting privileged communications and data from disclosure is paramount for legal teams. Legal advice, such as attorney-client communications or litigation strategy are typicall…
Empirical Comparisons of CNN with Other Learning Algorithms for Text Classification in Legal Document Review
Robert Keeling, Rishi Chhatwal, Nathaniel Huber-Fliflet +5
Research has shown that Convolutional Neural Networks (CNN) can be effectively applied to text classification as part of a predictive coding protocol. That said, most research to d…
An Empirical Study of the Application of Machine Learning and Keyword Terms Methodologies to Privilege-Document Review Projects in Legal Matters
Peter Gronvall, Nathaniel Huber-Fliflet, Jianping Zhang +3
Protecting privileged communications and data from disclosure is paramount for legal teams. Unrestricted legal advice, such as attorney-client communications or litigation strategy…
Explainable Text Classification in Legal Document Review A Case Study of Explainable Predictive Coding
Rishi Chhatwal, Peter Gronvall, Nathaniel Huber-Fliflet +3
In today's legal environment, lawsuits and regulatory investigations require companies to embark upon increasingly intensive data-focused engagements to identify, collect and analy…
Empirical Evaluations of Active Learning Strategies in Legal Document Review
Rishi Chhatwal, Nathaniel Huber-Fliflet, Robert Keeling +2
One type of machine learning, text classification, is now regularly applied in the legal matters involving voluminous document populations because it can reduce the time and expens…
Empirical Evaluations of Preprocessing Parameters' Impact on Predictive Coding's Effectiveness
Rishi Chhatwal, Nathaniel Huber-Fliflet, Robert Keeling +2
Predictive coding, once used in only a small fraction of legal and business matters, is now widely deployed to quickly cull through increasingly vast amounts of data and reduce the…