Attributes are visual concepts that can be detected by machines, understood by humans, and shared across categories. They are particularly useful for fine-grained domains where c...
Kun Duan, Devi Parikh, David J. Crandall, Kristen ...
In this paper, we consider a novel scheme referred to as Cartesian contour to concisely represent the collection of frequent itemsets. Different from the existing works, this sche...
Mining frequent patterns in a data stream is very challenging for the high complexity of managing patterns with bounded memory against the unbounded data. While many approaches as...
A new class of associations (polynomial itemsets and polynomial association rules) is presented which allows for discovering nonlinear relationships between numeric attributes wit...
Assessing the quality of discovered results is an important open problem in data mining. Such assessment is particularly vital when mining itemsets, since commonly many of the disc...