1. A method of correcting Optical Character Recognition (OCR) errors, comprising: converting a graphical representation of an original segment of text from a document into a first segment of text using a first OCR engine; converting the graphical representation of the original segment of text into a second segment of text using a second OCR engine; estimating an error probability for the first segment of text by matching the first segment of text with the second segment of text; responsive to the error probability exceeding a predetermined threshold value, generating a suspect interpretation, for the first segment of text, the suspect interpretation associated with a suspected OCR error; grouping the suspect interpretation with other similar suspect interpretations to form a cluster of suspect interpretations that are each associated with one or more occurrences of the suspected OCR error in the document; generating a representative question for the cluster; determining a correct answer for the representative question; and generating a corrected segment of text based on the correct answer, the corrected segment of text matching the original segment of text.
1. A method of correcting Optical Character Recognition (OCR) errors, comprising: converting a graphical representation of an original segment of text from a document into a first segment of text using a first OCR engine; converting the graphical representation of the original segment of text into a second segment of text using a second OCR engine; estimating an error probability for the first segment of text by matching the first segment of text with the second segment of text; responsive to the error probability exceeding a predetermined threshold value, generating a suspect interpretation, for the first segment of text, the suspect interpretation associated with a suspected OCR error; grouping the suspect interpretation with other similar suspect interpretations to form a cluster of suspect interpretations that are each associated with one or more occurrences of the suspected OCR error in the document; generating a representative question for the cluster; determining a correct answer for the representative question; and generating a corrected segment of text based on the correct answer, the corrected segment of text matching the original segment of text. 3. The method of claim 1 , further comprising: presenting the representative question to a human operator via a user interface; receiving the correct answer from the human operator; and applying the correct answer to all suspect interpretations in the cluster to generate corrected segments of text for the suspect interpretations in the cluster.