Aiming at a familiar and simple constraint that some items must or must not present in rules, a fast clippedtransaction-based constraint association-rule mining algorithm was put forward, This algorithm firstly scanned data base to clip transactions horizontally and vertically, then mined frequent item sets from clipped data set to form rules＇ candidate head sets, body sets and rule item sets. Finally, it scanned original data base again to gain association rules according to minimum confidence constraint. Experiments show that, compared with common st...
