Implementations of the well-known Apriori algorithm for finding frequent item sets and associations rules usually rely on a doubly recursive scheme to count the subsets of a given...
Discovering association rules that identify relationships among sets of items is an important problem in data mining. Finding frequent item sets is computationally the most expens...
Using concepts from rough set theory we investigate the existence of approximative descriptions of collections of objects that can be extracted from data sets, a problem of intere...
This paper considers the framework of the so-called "market basket problem", in which a database of transactions is mined for the occurrence of unusually frequent item s...
In this paper, we present a novel algorithm OpportuneProject for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. Our algorithm ...