  The Chaos Game Representation, a method for creating images from nucleotide
sequences, is modified to make images from chunks of text documents. Machine
learning methods are then applied to train classifiers based on authorship.
Experiments are conducted on several benchmark data sets in English, including
the widely used Federalist Papers, and one in Portuguese. Validation results
for the trained classifiers are competitive with the best methods in prior
literature. The methodology is also successfully applied for text
categorization with encouraging results. One classifier method is moreover seen
to hold promise for the task of digital fingerprinting.
