Active Learning for Constrained Dirichlet Process Mixture Models
Andreas G. Vlachos, Zoubin Ghahramani, Ted Briscoe · 2010
Recent work applied Dirichlet Process Mixture Models to the task of verb clustering, incorporating supervision in the form of must-links and cannot-links constraints between instances. In this work, we introduce an active learning approach for constraint selection employing uncertaintybased sampling. We achieve substantial improvements over random selection on two datasets. 1