1. A method of correcting Optical Character Recognition (OCR) errors, comprising: converting a graphical representation of an original segment of text 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; grouping the suspect interpretation with other similar suspect interpretations to form a cluster of suspect interpretations by: comparing the first segment of text with another segment of text of another suspect interpretation; responsive to the first segment of text matching the other segment of text, comparing the graphical representation of the original segment of text with a graphical representation of the other segment of text; and responsive to the graphical representation of the original segment of text being sufficiently similar to the graphical representation of the other segment of text, grouping the suspect interpretation with the other suspect interpretation in the cluster; 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.
6. The method of claim 1 , wherein estimating the error probability for the first segment of text further comprises: responsive to the first segment of text not matching the second segment of text, calculating the error probability for the first segment of text using a confidence level of the first segment of text and a confidence level of the second segment of text.