publication . Article . 2013

Cleaning OCR'd text with Regular Expressions

Laura Turner O'Hara;
Open Access English
  • Published: 01 May 2013
  • Publisher: Editorial Board of the Programming Historian
Abstract
Optical Character Recognition (OCR)—the conversion of scanned images to machine-encoded text—has proven a godsend for historical research. This process allows texts to be searchable on one hand and more easily parsed and mined on the other. But we’ve all noticed that the OCR for historic texts is far from perfect. Old type faces and formats make for unique OCR. How might we improve poor quality OCR? The answer is Regular Expressions or “regex.”
Subjects
free text keywords: Regular expressions, data manipulation, History (General), D1-2009, Computer software, QA76.75-76.765
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