dbacl is a digramic Bayesian text classifier. Given some text, it calculates the posterior probabilities that the input resembles one of any number of previously learned document collections. It can be used to sort incoming email into arbitrary categories such as spam, work, and play, or simply to distinguish an English text from a French text. It fully supports international character sets, and uses sophisticated statistical models based on the Maximum Entropy Principle.
Marko is a simple toolset that allows you to create markov chain databases of a corpus (or two) of text and then allows you to compare unknown texts to these databases. For any two marko databases you can calculate the probability that the unknown body is related to one over the other. Possible applications include intelligent mail filtering, plagiarism detection, and historical research.