14. A method for discovering association rules in a database using item constraints and items having a hierarchial taxonomy, the taxonomy defining descendant and ancestor relationships between the items, the method comprising: generating a set of selected items from a database based on predefined constraints, the predefined constraints involving one or more of the items in a mining input expression; determining a support value for an itemset; if the support value of the itemset is greater than a minimum support value and the itemset contains at least one of the selected items, determining the number of times the itemset appears in the database; entering the itemset into a set of large itemsets; outputting an association rule when the number of times the entered itemset appears in the database bears a predetermined relationship to a number of times an associated itemset appears in the database and thereby satisfies a minimum confidence constraint.
18. The method recited in claim 14, further comprising: forming a second itemset by concatenating the large itemsets with a set of large items in accordance with a predetermined concatenation regime to generate a set of candidate itemsets, where an item is large if the support value of the item is greater than a minimum support value; arranging the candidate itemsets so that each item within an itemset which is also contained in the set of selected items precedes any item not in the set of selected items; and using the set of candidate itemsets to output the association rules.