The effect of OCR errors on stylistic text classification

Authors:
Sterling Stuart Stein;Shlomo Argamon;Ophir Frieder
Affiliations:
Illinois Institute of Technology, Chicago, IL;Illinois Institute of Technology, Chicago, IL;Illinois Institute of Technology, Chicago, IL
Venue:
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Year:
2006

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Abstract

Recently, interest is growing in non-topical text classification tasks such as genre classification, sentiment analysis, and authorship profiling. We study to what extent OCR errors affect stylistic text classification from scanned documents. We find that even a relatively high level of errors in the OCRed documents does not substantially affect stylistic classification accuracy.