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Reviewing dupes for Continuous Active Learning in Relativity

When conducting active learning (CAL) in Relativity, keep in mind that you have a choice between whether or not the reviewers will be given documents which are textually similar to those which a coder has already determined to be responsive or non-responsive.

The Suppress Duplicate Documents setting should be set to Yes you are performing 'coverage review' in order to train the system as quickly as possible. In this model, the documents which the system is most uncertain about will be added to the review queue first - those with a rank around 50 on the scale from 0 to 100.

Prioritized review will prompt reviewers to focus on the highest ranking documents. When this type of review is performed the reviewers will code the highest ranking documents first.

Once a project has been started, the suppress duplicates setting cannot be changed.

The documents which are suppressed for a classification will be tagged in the field tree, so they can be reviewed earlier.


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