Shen, HongLiang, WeifaNg, Jack C2015-12-132015-12-130350-5596http://hdl.handle.net/1885/92090Many applications need to deal with the additive and multiplicative subcollections over a group of set families (databases). This paper presents two efficient algorithms for computing the frequent itemsets in these two types of subcollections respectively. Let T be a given subcollection of set families of total size m whose elements are drawn from a domain of size n. We show that ifT is an additive subcollection we can compute all frequent itemsets in T in O(m2n/(pn) + log p) time on an EREW PRAM with 1 ≤ p ≤ m2n/n processors, at a cost of maintaining the occurrences of all itemsets in each individual set family. If T is a multiplicative subcollection, we can compute all itemsets in T in O(mk/p + min {m′/p 2n, n3n log m′/p}) time on an EREW PRAM with 1 ≤ p ≤ min {m,2n} processors, where m′ = min {m,2n}. These present improvements over direct computation of the frequent itemsets on the subcollection concerned.Keywords: Algorithms; Database systems; Parallel processing systems; Program processors; Set theory; Frequent itemsets; Multiple set families; Data mining19992015-12-12