1. A computer-implemented method for creating an aggregate training data set corresponding to a document type, the method comprising: for each document of a document type in a set of documents: receiving the document type, wherein the document type identifies a type of content that is common to a plurality of documents of the set of documents; receiving input corresponding to a text sample in the document; receiving an image of the text sample in the document; for each of a plurality of candidate presentation styles: training an OCR processing engine using a training data set corresponding to the candidate presentation style; identifying text in the image of the text sample; producing OCR processing results for the document and the candidate presentation style using the OCR processing engine as trained; comparing the OCR processing results to the input corresponding to the text sample; and calculating a score for the candidate presentation style based on the comparison; ranking the candidate presentation styles based on the score calculated for each candidate presentation style; selecting a candidate presentation style for the document based on the ranking; and storing the selected candidate presentation style for the document with respect to the document type; and combining the training data set corresponding to the selected candidate presentation style for each document of the document type in the set of documents to create an aggregate training data set for the document type.
1. A computer-implemented method for creating an aggregate training data set corresponding to a document type, the method comprising: for each document of a document type in a set of documents: receiving the document type, wherein the document type identifies a type of content that is common to a plurality of documents of the set of documents; receiving input corresponding to a text sample in the document; receiving an image of the text sample in the document; for each of a plurality of candidate presentation styles: training an OCR processing engine using a training data set corresponding to the candidate presentation style; identifying text in the image of the text sample; producing OCR processing results for the document and the candidate presentation style using the OCR processing engine as trained; comparing the OCR processing results to the input corresponding to the text sample; and calculating a score for the candidate presentation style based on the comparison; ranking the candidate presentation styles based on the score calculated for each candidate presentation style; selecting a candidate presentation style for the document based on the ranking; and storing the selected candidate presentation style for the document with respect to the document type; and combining the training data set corresponding to the selected candidate presentation style for each document of the document type in the set of documents to create an aggregate training data set for the document type. 8. The method of claim 1 , wherein the candidate presentation styles each correspond to a text font and a text size.