Paper: Contextual Word Similarity And Estimation From Sparse Data

ACL ID P93-1022
Title Contextual Word Similarity And Estimation From Sparse Data
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1993
Authors

In recent years there is much interest in word cooccurrence relations, such as n-grams, verb- object combinations, or cooccurrence within a limited context. This paper discusses how to estimate the probability of cooccurrences that do not occur in the training data. We present a method that makes local analogies between each specific unobserved cooccurrence and other cooccurrences that contain simi- lar words, as determined by an appropriate word similarity metric. Our evaluation sug- gests that this method performs better than existing smoothing methods, and may provide an alternative to class based models.