White Papers

The Role of Remediation in Information Governance

Written by the Information Governance Initiative, this paper underscores the benefits of sorting and addressing the data your organization is currently storing-a logical beginning to any IG process.

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Common Statistical Concepts and Their Influence on Computer-Assisted Review

Dr. Gideon Frieder of George Washington University discusses how statistics—including basic concepts like probability, confidence intervals, and sampling—help make computer-assisted review defensible.

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Control Sets: Introducing Precision, Recall, and F1 into Relativity Assisted Review

In this paper, we investigate different ways to conduct—and measure the accuracy of—a computer-assisted review project using a control set workflow.

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Document Categorization Using Latent Semantic Indexing

This paper explains the engine behind Relativity Analytics, which uncovers document relationships based on concepts instead of just keywords.

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The Impact of Judgmental Sampling on Assisted Review

Dr. David Grossman explores how sample size and sampling methodology—including judgmental sampling based on keyword searches—affect the accuracy of a computer-assisted review project.

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Measuring and Validating the Effectiveness of Relativity Assisted Review

Dr. David Grossman investigates and explains reporting in Assisted Review, as well as the effectiveness and accuracy of the workflow.

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Understanding Security in Relativity Binders

This paper explains the multiple layers of Binders and iPad® security that keep your case documents safe inside the app.

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Understanding the Components of Assisted Review and the Workflow That Ties Them Together

This paper discusses how Assisted Review’s combination of experts, engine, and statistical validation produce defensible results with significant savings in review time and costs.

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