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...
We introduce a new algorithm for mining sequential patterns. Our algorithm is especially efficient when the sequential patterns in the database are very long. We introduce a novel...
Jay Ayres, Jason Flannick, Johannes Gehrke, Tomi Y...
Data mining can extract important knowledge from large data collections - but sometimes these collections are split among various parties. Privacy concerns may prevent the parties...
We introduce the notion of iceberg concept lattices and show their use in knowledge discovery in databases. Iceberg lattices are a conceptual clustering method, which is well suit...
Gerd Stumme, Rafik Taouil, Yves Bastide, Nicolas P...
Association rule mining (ARM) identifies frequent itemsets from databases and generates association rules by assuming that all items have the same significance and frequency of oc...