Konferensartikel

Clustering word senses from semantic mirroring data

Hamps Lilliehöök
Department of Computer and Information Science, Linköping University, Sweden

Magnus Merkel
Department of Computer and Information Science, Linköping University, Sweden

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

Linköping Electronic Conference Proceedings 88:4, s. 21-35

NEALT Proceedings Series 19:4, s. 21-35

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Publicerad: 2013-05-17

ISBN: 978-91-7519-586-5

ISSN: 1650-3686 (tryckt), 1650-3740 (online)

Abstract

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.

Nyckelord

Word senses; clustering; semantic mirroring

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