1. A method of minimizing surprisal data, the method comprising the steps of: a computer identifying characteristics of at least one data event; the computer receiving an input of rank of at least two identified characteristics of the at least one data event; the computer generating a hierarchy of ranked, identified characteristics based on the rank of the at least two identified characteristics of the at least one data event; the computer comparing the hierarchy of ranked, identified characteristics to a repository of characteristic context patterns each comprising a plurality of reference artifacts; when the hierarchy of ranked, identified characteristics matches at least one reference artifact from a characteristic context pattern in the repository, the computer storing the characteristic context pattern with the at least one matched reference artifact in a repository; the computer breaking the characteristic context pattern with the at least one matched reference artifact into pieces, at least some of the pieces being associated with the identified characteristics; the computer storing the pieces which are associated with the identified characteristics in the repository; the computer combining the stored pieces of the at least one matched reference artifacts into a surprisal context filter pattern with context determined to be probabilistically present within a specified degree of certainty in a data input; the computer comparing the data input to the surprisal context filter; the computer discarding the events from the data input that are the same as the context data for which the surprisal context filter selects; and the computer storing in a repository the events remaining in the data input as anomalous events.