By the same authors

Unsupervised Word Sense Disambiguation Using The WWW

Research output: Contribution to conferencePaper

Standard

Unsupervised Word Sense Disambiguation Using The WWW. / Klapaftis, Ioannis P.; Manandhar, Suresh.

2006. 174-183.

Research output: Contribution to conferencePaper

Harvard

Klapaftis, IP & Manandhar, S 2006, 'Unsupervised Word Sense Disambiguation Using The WWW' pp. 174-183.

APA

Klapaftis, I. P., & Manandhar, S. (2006). Unsupervised Word Sense Disambiguation Using The WWW. 174-183.

Vancouver

Klapaftis IP, Manandhar S. Unsupervised Word Sense Disambiguation Using The WWW. 2006.

Author

Klapaftis, Ioannis P. ; Manandhar, Suresh. / Unsupervised Word Sense Disambiguation Using The WWW.

Bibtex - Download

@conference{873788dc157f4d028d8e5614b2cde331,
title = "Unsupervised Word Sense Disambiguation Using The WWW",
abstract = "This paper presents a novel unsupervised methodology for automatic disambiguation of nouns found in unrestricted corpora. The proposed method is based on extending the context of a target word by querying the web, and then measuring the overlap of the extended context with the topic signatures of the different senses by using Bayes rule. The algorithm is evaluated on Semcor 2.0. The evaluation showed that the web-based extension of the target word's local context increases the amount of contextual information to perform semantic interpretation, in effect producing a disambiguation methodology, which achieves a result comparable to the performance of the best system in SENSEVAL 3.",
author = "Klapaftis, {Ioannis P.} and Suresh Manandhar",
year = "2006",
language = "Undefined/Unknown",
pages = "174--183",

}

RIS (suitable for import to EndNote) - Download

TY - CONF

T1 - Unsupervised Word Sense Disambiguation Using The WWW

AU - Klapaftis, Ioannis P.

AU - Manandhar, Suresh

PY - 2006

Y1 - 2006

N2 - This paper presents a novel unsupervised methodology for automatic disambiguation of nouns found in unrestricted corpora. The proposed method is based on extending the context of a target word by querying the web, and then measuring the overlap of the extended context with the topic signatures of the different senses by using Bayes rule. The algorithm is evaluated on Semcor 2.0. The evaluation showed that the web-based extension of the target word's local context increases the amount of contextual information to perform semantic interpretation, in effect producing a disambiguation methodology, which achieves a result comparable to the performance of the best system in SENSEVAL 3.

AB - This paper presents a novel unsupervised methodology for automatic disambiguation of nouns found in unrestricted corpora. The proposed method is based on extending the context of a target word by querying the web, and then measuring the overlap of the extended context with the topic signatures of the different senses by using Bayes rule. The algorithm is evaluated on Semcor 2.0. The evaluation showed that the web-based extension of the target word's local context increases the amount of contextual information to perform semantic interpretation, in effect producing a disambiguation methodology, which achieves a result comparable to the performance of the best system in SENSEVAL 3.

M3 - Paper

SP - 174

EP - 183

ER -