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Recognizing text genres with simple metrics using discriminant analysis
Open accessAbstract
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.
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Metadata
- Authors
- Karlgren, J., & Cutting, D.
- Venue
- Proceedings of the 15th conference on Computational linguistics -
- Published
- 1994
- Volume
- 2
- Pages
- 1071
- ISSN
- 1525-2477 (ISSN-L)
- OpenAlex
- W2038201841
- Cited by
- 293
- References
- 0
- FWCI
- 5.83
- Type
- conference paper
- Language
- en
- Open access
- bronze
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- Karlgren, J., & Cutting, D. (1994). Recognizing text genres with simple metrics using discriminant analysis. Proceedings of the 15th conference on Computational linguistics -. https://doi.org/10.3115/991250.991324
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