no code implementations • 16 Dec 2021 • Haozhen Zhao, Shi Ye, Jingchao Yang
Given the generalizable nature of privilege in legal cases, we hypothesize that transfer learning can capitalize knowledge learned from existing labeled data to identify privilege documents without requiring labeling new training data.
no code implementations • 16 Dec 2021 • Haozhen Zhao, Fusheng Wei, Hilary Quatinetz, Han Qin, Adam Dabrowski
During the past decade breakthroughs in GPU hardware and deep neural networks technologies have revolutionized the field of computer vision, making image analytical potentials accessible to a range of real-world applications.
no code implementations • 9 Feb 2021 • Rishi Chhatwal, Robert Keeling, Peter Gronvall, Nathaniel Huber-Fliflet, Jianping Zhang, Haozhen Zhao
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.
no code implementations • 5 Feb 2021 • Christian J. Mahoney, Katie Jensen, Fusheng Wei, Haozhen Zhao, Han Qin, Shi Ye
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.
no code implementations • 19 Dec 2019 • Robert Keeling, Rishi Chhatwal, Nathaniel Huber-Fliflet, Jianping Zhang, Fusheng Wei, Haozhen Zhao, Shi Ye, Han Qin
For each data set, classification models were trained with different training sample sizes using different learning algorithms.
no code implementations • 19 Dec 2019 • Nathaniel Huber-Fliflet, Fusheng Wei, Haozhen Zhao, Han Qin, Shi Ye, Amy Tsang
In this paper, we present several applications of deep learning in computer vision to Technology Assisted Review of image data in legal industry.
no code implementations • 19 Dec 2019 • Christian J. Mahoney, Jianping Zhang, Nathaniel Huber-Fliflet, Peter Gronvall, Haozhen Zhao
This paper describes a framework for explainable text classification as a valuable tool in legal services: for enhancing the quality and efficiency of legal document review and for assisting in locating responsive snippets within responsive documents.
no code implementations • 11 Jun 2019 • Christian J. Mahoney, Nathaniel Huber-Fliflet, Haozhen Zhao, Jianping Zhang, Peter Gronvall, Shi Ye
In this study, we use extensive experimentation to examine the impact of popular seed set selection strategies in active learning, within a predictive coding exercise, and evaluate different active learning strategies against well-researched continuous active learning strategies for the purpose of determining efficient training methods for classifying large populations quickly and precisely.
no code implementations • 3 Apr 2019 • Peter Gronvall, Nathaniel Huber-Fliflet, Jianping Zhang, Robert Keeling, Robert Neary, Haozhen Zhao
Overly-inclusive keyword searching can also be problematic, because even while it drives up costs, it also can cast `too far of a net' and thus produce unreliable results. To overcome these weaknesses of keyword searching, legal teams are using a new method to target privileged information called predictive modeling.
no code implementations • 3 Apr 2019 • Rishi Chhatwal, Nathaniel Huber-Fliflet, Robert Keeling, Jianping Zhang, Haozhen Zhao
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 expense associated with the review of those documents.
no code implementations • 3 Apr 2019 • Rishi Chhatwal, Nathaniel Huber-Fliflet, Robert Keeling, Jianping Zhang, Haozhen Zhao
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 need for costly and inefficient human document review.
no code implementations • 3 Apr 2019 • Fusheng Wei, Han Qin, Shi Ye, Haozhen Zhao
Predictive coding has been widely used in legal matters to find relevant or privileged documents in large sets of electronically stored information.
no code implementations • 3 Apr 2019 • 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.
no code implementations • 3 Apr 2019 • Rishi Chhatwal, Peter Gronvall, Nathaniel Huber-Fliflet, Robert Keeling, Jianping Zhang, Haozhen Zhao
In these scenarios, if predictive coding can be used to locate these responsive snippets, then attorneys could easily evaluate the model's document classification decision.
no code implementations • 21 Mar 2019 • Christian J. Mahoney, Nathaniel Huber-Fliflet, Katie Jensen, Haozhen Zhao, Robert Neary, Shi Ye
Since there is limited research on this important component of predictive coding, the authors of this paper set out to identify strategies that consistently perform well.