Paper: Bootstrapping via Graph Propagation

ACL ID P12-1065
Title Bootstrapping via Graph Propagation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2012

Bootstrapping a classifier from a small set of seed rules can be viewed as the propaga- tion of labels between examples via features shared between them. This paper introduces a novel variant of the Yarowsky algorithm based on this view. It is a bootstrapping learning method which uses a graph propagation algo- rithm with a well defined objective function. The experimental results show that our pro- posed bootstrapping algorithm achieves state of the art performance or better on several dif- ferent natural language data sets.