Abstract: A skipping natural language parser can include: identifying a candidate location within a string of characters with a processor, the candidate location being an unbroken string of relevant characters followed by an irrelevant character; attempting to parse an attribute from the candidate location with the processor; storing the attribute in a memory based on the attribute being parsed; skipping to a next candidate location based on the attribute being parsed with the processor; and skipping, the relevant characters of the candidate location and the irrelevant character following the candidate location, to the next candidate location based on the attribute not being parsed with the processor.

Abstract: A classification code parser and method can include: reading a classification code having a description; reading a required keyword, and a total number of keywords associated with the classification code; reading text of a note; tokenizing the text of the note to create a note token stream, the note token stream having a note token and a position of the note token within the note token stream; creating a keyword map including a total number of matched keywords; determining a match ratio from the total number of the matched keywords and the total number of the keywords; determining a proximity factor based on a shortest span of tokens within the note token stream containing all the matched keywords; and determining a strength of a match between the classification code and the note based on the match ratio being multiplied by the proximity factor.