SVD and clustering for unsupervised POS tagging

Michael Lamar*, Yariv Maron, Mark Johnson, Elie Bienenstock

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

16 Citations (Scopus)

Abstract

We revisit the algorithm of Schutze (1995) for unsupervised part-of-speech tagging. The algorithm uses reduced-rank singular value decomposition followed by clustering to extract latent features from context distributions. As implemented here, it achieves state-of-the-art tagging accuracy at considerably less cost than more recent methods. It can also produce a range of finer-grained taggings, with potential applications to various tasks.

Original languageEnglish
Title of host publicationACL 2010 - 48th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference
Place of PublicationStroudsburg, PA
PublisherAssociation for Computational Linguistics (ACL)
Pages215-219
Number of pages5
ISBN (Print)9781617388088
Publication statusPublished - 2010
Event48th Annual Meeting of the Association for Computational Linguistics, ACL 2010 - Uppsala, Sweden
Duration: 11 Jul 201016 Jul 2010

Other

Other48th Annual Meeting of the Association for Computational Linguistics, ACL 2010
CountrySweden
CityUppsala
Period11/07/1016/07/10

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    Lamar, M., Maron, Y., Johnson, M., & Bienenstock, E. (2010). SVD and clustering for unsupervised POS tagging. In ACL 2010 - 48th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (pp. 215-219). Stroudsburg, PA: Association for Computational Linguistics (ACL).