Improving Cause Detection Systems with Active Learning

Active learning has been successfully applied to many natural language processing tasks for obtaining annotated data in a cost-effective manner. We propose several extensions to an active learner that adopts the margin-based uncertainty sampling framework. Experimental results on a cause detection problem involving the classification of aviation safety reports demonstrate the effectiveness of our extensions.

• Type: Journal
• Year: 2010
• Where: CIDU
• Authors: Isaac Persing, Vincent Ng
• Keywords: Active Learner, Cause Detection Problem, CIDU 2010, Cost-effective Manner, Machine Learning