We introduce a new kind of patterns, called emerging patterns (EPs), for knowledge discovery from databases. EPs are defined as itemsets whose supports increase significantly from...
In this work we focus on the problem of frequent itemset mining on large, out-of-core data sets. After presenting a characterization of existing out-of-core frequent itemset minin...
Previous studies have presented convincing arguments that a frequent pattern mining algorithm should not mine all frequent patterns but only the closed ones because the latter lea...
The support-confidence framework is the most common measure used in itemset mining algorithms, for its antimonotonicity that effectively simplifies the search lattice. This com...
Detection of interactions among data items constitutes an essential part of knowledge discovery. The cascade model is a rule induction methodology using levelwise expansion of a la...