most citedEmpirical Study of Deep Learning for Text Classification in Legal Document Review

99 citations · 108 across the 4 of their papers we have counts for

collaborators

5 papers

cs.IR2021

Application of Deep Learning in Recognizing Bates Numbers and Confidentiality Stamping from Images

Christian J. Mahoney, Katie Jensen, Fusheng Wei +3

In eDiscovery, it is critical to ensure that each page produced in legal proceedings conforms with the requirements of court or government agency production requests. Errors in pro…

cs.CV2019

Image Analytics for Legal Document Review: A Transfer Learning Approach

Nathaniel Huber-Fliflet, Fusheng Wei, Haozhen Zhao +3

Though technology assisted review in electronic discovery has been focusing on text data, the need of advanced analytics to facilitate reviewing multimedia content is on the rise.…

cs.IR20196 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.IR20193 cited

Using Google Analytics to Support Cybersecurity Forensics

Han Qin, Kit Riehle, Haozhen Zhao

Web traffic is a valuable data source, typically used in the marketing space to track brand awareness and advertising effectiveness. However, web traffic is also a rich source of i…

cs.IR201999 cited

Empirical Study of Deep Learning for Text Classification in Legal Document Review

Fusheng Wei, Han Qin, Shi Ye +1

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 sign…