Although OCR technology is now commonplace, character recognition errors are still a problem, in particular, in automated systems for information extraction from printed documents. This paper proposes a method for the automatic detection and correction of OCR errors in an information extraction system. Our algorithm uses domain-knowledge about possible misrecognition of characters to propose corrections; then it exploits knowledge about the type of the extracted information to perform syntactic and semantic checks in order to validate the proposed corrections.
We assess our proposal on a real-world, highly challenging dataset composed of nearly 800 values extracted from approximately 100 commercial invoices and we obtained very good results.
