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...
Multiple pairwise comparisons are one of the most frequent tasks in applied statistics. In this context, letter displays may be used for a compact presentation of results of multi...
Abstract-- We present COLR-Tree, an abstraction layer designed to support efficient spatio-temporal queries on live data gathered from a large collection of sensors. We use COLR-Tr...
This paper presents the implementation of kDCI, an enhancement of DCI [10], a scalable algorithm for discovering frequent sets in large databases. The main contribution of kDCI re...
Salvatore Orlando, Claudio Lucchese, Paolo Palmeri...
During the last few years more and more functionalities of RNA have been discovered that were previously thought of being carried out by proteins alone. One of the most striking di...
Patrick May, Gunnar W. Klau, Markus Bauer, Thomas ...