Paper: SenseClusters: Unsupervised Clustering And Labeling Of Similar Contexts

ACL ID P05-3027
Title SenseClusters: Unsupervised Clustering And Labeling Of Similar Contexts
Venue Annual Meeting of the Association of Computational Linguistics
Session System Demonstration
Year 2005
Authors

SenseClusters is a freely available system that identifies similar contexts in text. It relies on lexical features to build first and second order representations of contexts, which are then clustered using unsuper- vised methods. It was originally devel- oped to discriminate among contexts cen- tered around a given target word, but can now be applied more generally. It also supports methods that create descriptive and discriminating labels for the discov- ered clusters.