Paper: Bayesian Word Sense Induction

ACL ID E09-1013
Title Bayesian Word Sense Induction
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2009

Sense induction seeks to automatically identify word senses directly from a cor- pus. A key assumption underlying pre- vious work is that the context surround- ing an ambiguous word is indicative of its meaning. Sense induction is thus typ- ically viewed as an unsupervised cluster- ing problem where the aim is to partition a word’s contexts into different classes, each representing a word sense. Our work places sense induction in a Bayesian con- text by modeling the contexts of the am- biguous word as samples from a multi- nomial distribution over senses which are in turn characterized as distributions over words. The Bayesian framework pro- vides a principled way to incorporate a wide range of features beyond lexical co- occurrences and to systematically assess their utility on the sens...