Private itemset support counting (PISC) is a basic building block of various privacy-preserving data mining algorithms. Briefly, in PISC, Client wants to know the support of her i...
In data mining applications, highly sized contexts are handled what usually results in a considerably large set of frequent itemsets, even for high values of the minimum support t...
Tarek Hamrouni, Sadok Ben Yahia, Engelbert Mephu N...
Many researchers in our community (this author included) regularly emphasize the role constraints play in improving performance of data-mining algorithms. This emphasis has led to ...
Existing association rule mining algorithms suffer from many problems when mining massive transactional datasets. Some of these major problems are: (1) the repetitive I/O disk sca...
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is b...
Adam Kirsch, Michael Mitzenmacher, Andrea Pietraca...