System and method for electronic document classification

A computer program product loaded on a non-transitory computer readable medium, which when executed, classifies electronic documents, comprising program code for:

• converting a hypertext markup language (HTML) candidate electronic document comprising character data to a single candidate image, the converting including extracting a body section of the HTML candidate electronic document and converting the entire body section of the HTML candidate electronic document into the single candidate image;
• scaling the entire single candidate image to a size substantially smaller than an original size of the candidate image to provide a single scaled candidate image;
• obtaining a representation of a degree of visual similarity of the single entire scaled candidate image to a reference image by performing a single comparison of the entire single scaled candidate image to the entire reference image, the reference image having been obtained by identifying a reference electronic document containing character data representative of a specified classification;
• automatically classifying the candidate electronic document under the specified classification when the degree of visual similarity exceeds a predetermined threshold and, in response to the degree of visual similarity exceeding the predetermined threshold, converting the reference electronic document to a reference image;
• and
• determining an efficiency of the classifying by comparing a number of candidate electronic documents that are automatically classified under the specified classification to a number of candidate electronic documents that a user classifies under the specified classification.

A computer-implemented method for classifying electronic documents comprising:

• converting a hypertext markup language (HTML) candidate electronic document comprising character data to a single candidate image, the converting including extracting a body section of the HTML candidate electronic document and converting the entire body section of the HTML candidate electronic document into the single candidate image;
• scaling the entire single candidate image to a size substantially smaller than an original size of the candidate image to provide a single scaled candidate image;
• obtaining a representation of a degree of visual similarity of the single entire scaled candidate image to a reference image by performing a single comparison of the entire single scaled candidate image to the entire reference image, the reference image having been obtained by identifying a reference electronic document containing character data representative of a specified classification;
• automatically classifying the candidate electronic document under the specified classification when the degree of visual similarity exceeds a predetermined threshold and, in response to the degree of visual similarity exceeding the predetermined threshold, converting the reference electronic document to a reference image;
• and
• determining an efficiency of the classifying by comparing a number of candidate electronic documents that are automatically classified under the specified classification to a number of candidate electronic documents that a user classifies under the specified classification.