11. The method according to claim 1 , further comprising: determining whether to perform machine learning upon identification of said at least one optimal sub-sequence; if machine learning is elected, collecting said optimal sub-sequence and other terms; specifying a training set for training a binary classifier; predicting the category of all enumerated terms; associating a category weight for each of said enumerated terms, said weight comprising the predicted category of each of said enumerated terms; and computing the longest increasing sub-sequence.
1. A method for operating a computing device to create a document structure model of a computer parsable text document utilizing recognition of at least one ordered sequence of identifiers in the document, the method comprising: navigating to a document conversion graphical user interface; converting at least one computer parsable text document of any format to an alternative structured language format to form a converted document; fragmenting the text of said converted document, wherein fragmenting comprises breaking said converted document into an ordered sequence of text fragments within a text format; enumerating said text fragments to obtain a sequence of terms, wherein each said term comprises a matching fragment; identifying at least one optimal sub-sequence of terms, wherein said optimal sub-sequence comprises at least one longest increasing sub-sequence from among said sequence of terms; annotating the computer parsable text document with tags, wherein said tags comprise information derived from identification of said at least one optimal sub-sequence; and displaying said annotated document on said graphical user interface.