The aim of this short paper is to present a general method of using background knowledge to impose constraints in conceptual clustering of object-attribute relational data. The pr...
The output of boolean association rule mining algorithms is often too large for manual examination. For dense datasets, it is often impractical to even generate all frequent items...
Condensed representations of pattern collections have been recognized to be important building blocks of inductive databases, a promising theoretical framework for data mining, and...
Abstract. In this paper we aim at extending the non-derivable condensed representation in frequent itemset mining to sequential pattern mining. We start by showing a negative examp...
Since transaction identifiers (ids) are unique and would not usually be frequent, mining frequent patterns with transaction ids, showing records they occurred in, provides an effic...