6. A method for classifying a genre of an electronic document, comprising: receiving an electronic document; converting the electronic document to rich text format (RTF) using optical character recognition technology; parsing the RTF document into lines of text ordered from top to bottom and left to right, and into line separators based on space between blocks of the lines of text; assigning tokens to each of the lines of text based on the content the line of text and to each of the line separators; sequencing the tokens; parsing the tokenized document with a number of pre-defined document grammars; determining a probability for each genre corresponding to the electronic document based on the parsed tokenized document; classifying the electronic document as the genre with the highest probability; and routing the electronic document to at least one output device based on the classification.
6. A method for classifying a genre of an electronic document, comprising: receiving an electronic document; converting the electronic document to rich text format (RTF) using optical character recognition technology; parsing the RTF document into lines of text ordered from top to bottom and left to right, and into line separators based on space between blocks of the lines of text; assigning tokens to each of the lines of text based on the content the line of text and to each of the line separators; sequencing the tokens; parsing the tokenized document with a number of pre-defined document grammars; determining a probability for each genre corresponding to the electronic document based on the parsed tokenized document; classifying the electronic document as the genre with the highest probability; and routing the electronic document to at least one output device based on the classification. 7. The method of claim 6 , wherein the output device is one of a server, a personal computer, or a personal digital assistant.