Similarity-Based Methods for Word Sense Disambiguation

We compare four similarity-based estimation methods against back-off and maximum-likelihood estimation methods on a pseudo-word sense disambiguation task in which we controlled for both unigram and bigram frequency. The similarity-based methods perform up to 40% better on this particular task. We also conclude that events that occur only once in the training set have major impact on similarity-based estimates.

• Type: Conference
• Year: 1997
• Where: ACL
• Authors: Ido Dagan, Lillian Lee, Fernando C. N. Pereira
• Keywords: ACL 1997, ACL 2007, Estimation Methods, Maximum-likelihood Estimation Methods, Similarity-based Estimation Methods