Changes

According to “Project Goal V2,” (E:\mcnair\Projects\Incubators) there are three proposed methods to organize and extract useful information from an HTML web page. The first method is textual text processing, analyzing and classifying the text textual content of the HTML page either through a Word2Vec or “Bag of Words” approach. The second method is to use image based pattern recognition, likely through an off-the-shelf model that can extrapolate key HTML elements from web page screenshots. The third, and most novel method is to structurally analyze the HTML tree structure, and express that simplified HTML structure in a Domain Specific Language (DSL).  === Text Processing === There are two possible classification methods for the processing the text of target HTML pages. The first is a "Bag of Words" approach, which uses Term Frequency – Inverse Document Frequency to do basic natural language processing and select words or phrases which have discriminant capabilities. The second is a Word2Vec approach which uses shallow 2 layer neural networks to reduce descriptions to a vector with high discriminant potential. (See "Memo for Evan" in E:\mcnair\Projects\Incubators for further detail.)