Traditional data mining applications consider the problem of mining a single relation between two attributes. For example, in a scientific bibliography database, authors are rela...
Foto N. Afrati, Gautam Das, Aristides Gionis, Heik...
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
We study the following variant of the bin covering problem. We are given a set of unit sized items, where each item has a color associated with it. We are given an integer paramet...
For a finite set of points S, the (monochromatic) Reverse Nearest Neighbor (RNN) rule associates with any query point q the subset of points in S that have q as its nearest neighb...