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CNN Application in Detection of Privileged Documents in Legal Document Review by Chhatwal, Rishi; Keeling, Robert; Gronvall, Peter; Huber-Fliflet, Nathaniel; Zhang, Jianping; Zhao, Haozhen is a scholarly article available to read on EtoBox.

What is CNN Application in Detection of Privileged Documents in Legal Document Review about?

Protecting privileged communications and data from disclosure is paramount for legal teams. Legal advice, such as attorney-client communications or litigation strategy are typically exempt from disclosure in litigations or regulatory events and are vital to the attorney-client relationship. To protect this information from disclosure, companies and outside counsel often review vast amounts of documents to determine those that contain privileged material. This process is extremely costly and time consuming. As data volumes increase, legal counsel normally employs methods to reduce the number of documents requiring review while balancing the need to ensure the protection of privileged information. Keyword searching is relied upon as a method to target privileged information and reduce document review populations. Keyword searches are effective at casting a wide net but often return overly inclusive results - most of which do not contain privileged information. To overcome the weaknesses of keyword searching, legal teams increasingly are using machine learning techniques to target privileged information. In these studies, classic text classification techniques are applied to build cla

Author

Chhatwal, Rishi; Keeling, Robert; Gronvall, Peter; Huber-Fliflet, Nathaniel; Zhang, Jianping; Zhao, Haozhen

Published

2021

Language

EN