Probabilistic frequent itemset mining in uncertain transaction databases semantically and computationally differs from traditional techniques applied to standard "certain&quo...
Inductive databases (IDBs) have been proposed to afford the problem of knowledge discovery from huge databases. With an IDB the user/analyst performs a set of very different operat...
In this paper we study when the disclosure of data mining results represents, per se, a threat to the anonymity of the individuals recorded in the analyzed database. The novelty o...
Maurizio Atzori, Francesco Bonchi, Fosca Giannotti...
In this paper we study a new problem in temporal pattern mining: discovering frequent arrangements of temporal intervals. We assume that the database consists of sequences of even...
Panagiotis Papapetrou, George Kollios, Stan Sclaro...
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...