Paper: Closing the Loop: Fast Interactive Semi-Supervised Annotation With Queries on Features and Instances

ACL ID D11-1136
Title Closing the Loop: Fast Interactive Semi-Supervised Annotation With Queries on Features and Instances
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2011
Authors

This paper describes DUALIST, an active learning annotation paradigm which solicits and learns from labels on both features (e.g., words) and instances (e.g., documents). We present a novel semi-supervised training al- gorithm developed for this setting, which is (1) fast enough to support real-time interac- tive speeds, and (2) at least as accurate as pre- existing methods for learning with mixed fea- ture and instance labels. Human annotators in user studies were able to produce near-state- of-the-art classifiers—on several corpora in a variety of application domains—with only a few minutes of effort.