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Recognizing Text Genres with Simple Metrics Using Discriminant Analysis
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.ORCID iD: 0000-0003-4042-4919
1994 (English)In: Proceedings of the 15th International Conference on Computational Linguistics, 1994, Vol. 2, 1071-1075 p.Conference paper (Refereed)
Abstract [en]

A simple method for categorizing texts into pre-determined text genre categories using the statistical standard technique of discriminant analysis is demonstrated with application to the Brown corpus. Discriminant analysis makes it possible use a large number of parameters that may be specific for a certain corpus or information stream, and combine them into a small number of functions, with the parameters weighted on basis of how useful they are for discriminating text genres. An application to information retrieval is discussed.

Place, publisher, year, edition, pages
1994. Vol. 2, 1071-1075 p.
National Category
Language Technology (Computational Linguistics)
URN: urn:nbn:se:kth:diva-116341DOI: 10.3115/991250.991324OAI: diva2:775526
International Conference on Computational Linguistics (Coling)

QC 20150327. 20160314

Available from: 2015-01-03 Created: 2013-01-16 Last updated: 2016-03-14Bibliographically approved

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Karlgren, Jussi
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