{'fraction_non_alphanumeric': 0.02459791863765374, 'fraction_numerical': 0.004730368968779565, 'mean_word_length': 4.910614525139665, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Program Proposal for Ph . D . in Computer Science “ Voracious Classifiers ” May 8 , 2006

The “Digital Age” has not led to a paperless office or rendered hard copies of documents obsolete as some predicted. If anything, it seems this appreciation of the necessity and value these documents have has raised the accessibility and distribution of non-digital documents. However, this increase in accessibility also leads to an overload of information as the rate at which documents can be obtained and digitized exceeds the rate at which sense (context, content, etc) can be made of documents. Existing methods for extracting content from document images are limited in several ways: they don’t yet perform well on the full diversity of document and content types, and they are incapable of being trained on the huge collections of document images now rapidly being scanned in (by Google, Amazon, and others). This proposal suggests a research program that achieves high speed classification of document image content utilizing extremely large scale data sets.