The staggering growth in smartphone and wearable device use has led to a massive scale
generation of personal (user-specific) data. To explore, analyze, and extract useful …

In data mining, Frequent Itemsets Mining is a technique used in several domains with
notable results. However, the large volume of data in modern datasets increases the …

In spite of the omnipresence of parallel (multi-core) systems, the predominant strategy to
evaluate window-based stream joins is still strictly sequential, mostly just straightforward …

Complex event detection is an advanced form of data stream processing where the stream
(s) are scrutinized to identify given event patterns. The challenge for many complex event …

Field-programmable gate arrays (FPGAs) are a promising technology that can be used in
database systems. In this demonstration we show Glacier, a library and a compiler that can …

MapReduce, originally developed by Google for search applications, has recently become a
popular programming framework for parallel and distributed environments. This paper …

Histograms are a crucial part of database query planning but their computation is resource-
intensive. As a consequence, generating histograms on database tables is typically …

Sketching algorithms are a powerful tool for single-pass data summarization. Their
numerous applications include approximate query processing, machine learning, and large …

Computing frequent items is an important problem by itself and as a subroutine in several
data mining algorithms. In this paper, we explore how to accelerate the computation of …

The increasing number of cores and the rich instruction sets of modern hardware are
opening up new opportunities for optimizing many traditional data mining tasks. In this paper …