21 December 2000 Evaluating text categorization in the presence of OCR errors
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In this paper we describe experiments that investigate the effects of OCR errors on text categorization. In particular, we show that in our environment, OCR errors have no effect on categorization when we use a classifier based on the naive Bayes model. We also observe that dimensionality reduction techniques eliminate a large number of OCR errors and improve categorization results.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kazem Taghva, Kazem Taghva, Thomas A. Nartker, Thomas A. Nartker, Julie Borsack, Julie Borsack, Steven Lumos, Steven Lumos, Allen Condit, Allen Condit, Ron Young, Ron Young, } "Evaluating text categorization in the presence of OCR errors", Proc. SPIE 4307, Document Recognition and Retrieval VIII, (21 December 2000); doi: 10.1117/12.410861; https://doi.org/10.1117/12.410861


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