Multi-Faceted Recall of Continuous Active Learning for Technology-Assisted Review

Gordon V. Cormack & Maura R. Grossman

Accepted for publication at SIGIR 2015.

Abstract

Continuous active learning achieves high recall for technology-assisted review, not only for an overall information need, but also for various facets of that information need, whether explicit or implicit. Through simulations using Cormack and Grossman's TAR Evaluation Toolkit (SIGIR 2014), we show that continuous active learning, applied to a multi-faceted topic, efficiently achieves high recall for each facet of the topic. Our results assuage the concern that continuous active learning may achieve high overall recall at the expense of excluding identifiable categories of relevant information.