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CNN Application in Detection of Privileged Documents in Legal Document Review
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.
Empirical Comparisons of CNN with Other Learning Algorithms for Text Classification in Legal Document Review
For each data set, classification models were trained with different training sample sizes using different learning algorithms.
Empirical Evaluations of Active Learning Strategies in Legal Document Review
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.
Explainable Text Classification in Legal Document Review A Case Study of Explainable Predictive Coding
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.
Empirical Evaluations of Preprocessing Parameters' Impact on Predictive Coding's Effectiveness
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.
