<P> GUHA is a general method for exploratory data analysis that has theoretical foundations in observational calculi . </P> <P> The ASSOC procedure is a GUHA method which mines for generalized association rules using fast bitstrings operations . The association rules mined by this method are more general than those output by apriori, for example "items" can be connected both with conjunction and disjunctions and the relation between antecedent and consequent of the rule is not restricted to setting minimum support and confidence as in apriori: an arbitrary combination of supported interest measures can be used . </P> <P> OPUS is an efficient algorithm for rule discovery that, in contrast to most alternatives, does not require either monotone or anti-monotone constraints such as minimum support . Initially used to find rules for a fixed consequent it has subsequently been extended to find rules with any item as a consequent . OPUS search is the core technology in the popular Magnum Opus association discovery system . </P> <P> A famous story about association rule mining is the "beer and diaper" story . A purported survey of behavior of supermarket shoppers discovered that customers (presumably young men) who buy diapers tend also to buy beer . This anecdote became popular as an example of how unexpected association rules might be found from everyday data . There are varying opinions as to how much of the story is true . Daniel Powers says: </P>

Association rule mining is an example of supervised learning