SenseClusters - Finding clusters that represent word senses

Amruta Purandare, Ted Pedersen

Research output: Contribution to conferencePaperpeer-review

13 Scopus citations

Abstract

SenseClusters is a freely available word sense discrimination system that takes a purely unsupervised clustering approach. It uses no knowledge other than what is available in a raw unstructured corpus, and clusters instances of a given target word based only on their mutual contextual similarities. It is a complete system that provides support for feature selection from large corpora, several different context representation schemes, various clustering algorithms, and evaluation of the discovered clusters.

Original languageEnglish (US)
Pages26-29
Number of pages4
StatePublished - 2004
Event2004 Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics - Demonstrations, HLT-NAACL 2004 - Boston, United States
Duration: May 2 2004May 7 2004

Conference

Conference2004 Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics - Demonstrations, HLT-NAACL 2004
Country/TerritoryUnited States
CityBoston
Period5/2/045/7/04

Bibliographical note

Funding Information:
This work has been partially supported by a National Science Foundation Faculty Early CAREER Development award (Grant #0092784).

Publisher Copyright:
© HLT-NAACL 2004 - Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, Demonstrations. All rights reserved.

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