Abstract
One of the challenges of data mining is revealing the interesting if-then rules in the mined dataset. We present two methods for the automated discovery of unexpected, and, thereby, interesting rules within the set of all the if-then rules previously revealed in the dataset. The first method calculates, for each rule, the probability that the rule exists accidentally. The lower this probability, the more unexpected the rule is. The second method calculates the conditional probability of the event described by the rule, given the relevant more basic rules. Once again, the lower this conditional probability, the more unexpected the rule is. These two methods are independent and can be combined.