Similarity-based methods for word sense disambiguation

I. Dagan; Lillian Lee; Fernando Pereira

Similarity-based methods for word sense disambiguation

I. Dagan, Lillian Lee, Fernando Pereira

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	American English
Title of host publication	The 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Publisher	Association for Computational Linguistics
State	Published - 1997

Bibliographical note

Place of conference:Madrid, Spain

Cite this

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title = "Similarity-based methods for word sense disambiguation",

abstract = "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.",

author = "I. Dagan and Lillian Lee and Fernando Pereira",

note = "Place of conference:Madrid, Spain",

year = "1997",

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booktitle = "The 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics",

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Similarity-based methods for word sense disambiguation. / Dagan, I.; Lee, Lillian; Pereira, Fernando.
The 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, 1997.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Similarity-based methods for word sense disambiguation

AU - Dagan, I.

AU - Lee, Lillian

AU - Pereira, Fernando

N1 - Place of conference:Madrid, Spain

PY - 1997

Y1 - 1997

N2 - 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.

AB - 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.

UR - https://scholar.google.co.il/scholar?q=Similarity-based+methods+for+word+sense+disambiguation+&btnG=&hl=en&as_sdt=0%2C5

M3 - Conference contribution

BT - The 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics

PB - Association for Computational Linguistics

ER -

Similarity-based methods for word sense disambiguation

Abstract

Bibliographical note

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