Similarity-based methods for word sense disambiguation

被引：57

作者：

Dagan, I ^{[1
]}

Lee, L ^{[1
]}

Pereira, F ^{[1
]}

机构：

[1] Bar Ilan Univ, Dept Math & Comp Sci, IL-52900 Ramat Gan, Israel

来源：

35TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS AND THE 8TH CONFERENCE OF THE EUROPEAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, PROCEEDINGS OF THE CONFERENCE | 1997年

关键词：

D O I：

10.3115/979617.979625

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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 perforin 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.

引用

页码：56 / 63

页数：8