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Both handwriting recognition systems and their users are error prone. Handwriting recognizers make recognition errors, and users may miss those errors when verifying output. As a result, it is common for recognized documents to contain <i>residual errors</i>. Unfortunately, in some application domains (e.g. health informatics), tolerance for residual errors(More)
Handwriting recognizers occasionally misinterpret digital ink input, requiring users to compare their ink input and the recognizer output to identify and correct errors. Technologies like Anoto pens can make this error discovery and correction task more difficult, because verification of recognizer output may occur many hours after data input and may(More)
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