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The Impact of Incorrect Training Sets and Rolling Collections on Technology-Assisted Review (TAR) and Defensible Disposition

At the conference we submitted recent Technology Assisted Review (TAR) findings described in the paper “The Impact of Incorrect Training Sets and Rolling Collections on Technology-Assisted Review, which was written by Mary Mack, Tim van Cann and myself. In this paper, the findings presented show that training samples can have a very large margin of error before they impact TAR results unacceptably, but that documents added to a review set after training the classifiers, do result in an unacceptable TAR error rate. Document classification and machine learning technology in eDiscovery are gaining attention under new names such as technology-assisted review (TAR), machine-assisted review (MAR), computer-assisted review (CAR) and predictive coding

Johannes Scholtes's profile image

Blog Entry
Using Machine Aided Indexing To Increase Accountability

The MAI can be set to tag any documents that would present ethical or legal problems and a compliance review could take place with both internal staff members and other external eyes

Jeff Lewis's profile image