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20192025
most citedExplainable Text Classification in Legal Document Review A Case Study of Explainable Predictive Coding

36 citations · 105 across the 17 of their papers we have counts for

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Showing 2019Show all

7 papers · 1 filter

cs.IR2019★ 7 cited

A Framework for Explainable Text Classification in Legal Document Review

Christian J. Mahoney, Jianping Zhang, Nathaniel Huber-Fliflet +2

Companies regularly spend millions of dollars producing electronically-stored documents in legal matters. Recently, parties on both sides of the 'legal aisle' are accepting the use…

cs.IR2019★ 6 cited

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…

cs.IR2019

Evaluation of Seed Set Selection Approaches and Active Learning Strategies in Predictive Coding

Christian J. Mahoney, Nathaniel Huber-Fliflet, Haozhen Zhao +3

Active learning is a popular methodology in text classification - known in the legal domain as "predictive coding" or "Technology Assisted Review" or "TAR" - due to its potential t…

cs.IR2019★ 2 cited

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…

cs.IR2019★ 36 cited

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…

cs.IR2019★ 18 cited

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…

cs.IR2019★ 27 cited

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…