Article | Proceedings of the workshop on lexical semantic resources for NLP at NODALIDA 2013; May 22-24; 2013; Oslo; Norway. NEALT Proceedings Series 19 | Clustering word senses from semantic mirroring data
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Title:
Clustering word senses from semantic mirroring data
Author:
Hamps Lilliehöök: Department of Computer and Information Science, Link√∂ping University, Sweden Magnus Merkel: Department of Computer and Information Science, Link√∂ping University, Sweden
Download:
Full text (pdf)
Year:
2013
Conference:
Proceedings of the workshop on lexical semantic resources for NLP at NODALIDA 2013; May 22-24; 2013; Oslo; Norway. NEALT Proceedings Series 19
Issue:
088
Article no.:
004
Pages:
21-35
No. of pages:
15
Publication type:
Abstract and Fulltext
Published:
2013-05-17
ISBN:
978-91-7519-586-5
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Series:
NEALT Proceedings Series
Publisher:
Linköping University Electronic Press; Linköpings universitet


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In this article we describe work on creating word clusters in two steps. First; a graph-based approach to semantic mirroring is used to create primary synonym clusters from a bilingual lexicon. Secondly; the data is represented by vectors in a large vector space and a resource of synonym clusters is then constructed by performing K-means centroid-based clustering on the vectors. We evaluate the results automatically against WordNet and evaluate a sample of word clusters manually. Prospects and applications of the approach are also discussed.

Keywords: Word senses; clustering; semantic mirroring

Proceedings of the workshop on lexical semantic resources for NLP at NODALIDA 2013; May 22-24; 2013; Oslo; Norway. NEALT Proceedings Series 19

Author:
Hamps Lilliehöök, Magnus Merkel
Title:
Clustering word senses from semantic mirroring data
References:

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Proceedings of the workshop on lexical semantic resources for NLP at NODALIDA 2013; May 22-24; 2013; Oslo; Norway. NEALT Proceedings Series 19

Author:
Hamps Lilliehöök, Magnus Merkel
Title:
Clustering word senses from semantic mirroring data
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