Networks of thousands of sensors present a feasible and economic solution to some of our most challenging problems, such as real-time traffic modeling, military sensing and trackin...
Abstract In this paper we propose a novel parallel algorithm for frequent itemset mining. The algorithm is based on the filter-stream programming model, in which the frequent item...
Adriano Veloso, Wagner Meira Jr., Renato Ferreira,...
Frequent itemset mining is a core data mining operation and has been extensively studied over the last decade. This paper takes a new approach for this problem and makes two major...
Recently, the data stream, which is an unbounded sequence of data elements generated at a rapid rate, provides a dynamic environment for collecting data sources. It is likely that ...
In this paper, we present the foundations for mining frequent tri-concepts, which extend the notion of closed itemsets to three-dimensional data to allow for mining folksonomies. ...