Paper: Inducing Domain-Specific Semantic Class Taggers from (Almost) Nothing

ACL ID P10-1029
Title Inducing Domain-Specific Semantic Class Taggers from (Almost) Nothing
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2010
Authors

This research explores the idea of inducing domain-specific semantic class taggers us- ing only a domain-specific text collection and seed words. The learning process be- gins by inducing a classifier that only has access to contextual features, forcing it to generalize beyond the seeds. The contex- tual classifier then labels new instances, to expand and diversify the training set. Next, a cross-category bootstrapping pro- cess simultaneously trains a suite of clas- sifiers for multiple semantic classes. The positive instances for one class are used as negative instances for the others in an it- erative bootstrapping cycle. We also ex- plore a one-semantic-class-per-discourse heuristic, and use the classifiers to dynam- ically create semantic features. We eval- uate our approach by induci...