Social networks are real‐time platforms formed by users involving conversations and
interactions. This phenomenon of the new information era results in a very huge amount of …

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 this work, we describe a range of prototy** boards such as Arduino, Raspberry Pi, and
BeagleBone Black, and we show how these devices are being used in our ECE curriculum …

The Web is a constantly expanding global information space that includes disparate types of
data and resources. Recent trends demonstrate the urgent need to manage the large …

Sorting is a fundamental operation in computer science and is a bottleneck in many
important fields. Sorting is critical to database applications, online search and indexing …

We present a message-passing based parallel version of the Space Saving algorithm
designed to solve the k–majority problem. The algorithm determines in parallel frequent …

We deal with the problem of detecting frequent items in a stream under the constraint that
items are weighted, and recent items must be weighted more than older ones. This kind of …

The problem of mining correlated heavy hitters (CHH) from a two-dimensional data stream
has been introduced recently, and a deterministic algorithm based on the use of the Misra …

We present FDCMSS, a new sketch-based algorithm for mining frequent items in data
streams. The algorithm cleverly combines key ideas borrowed from forward decay, the …

We present four CUDA based parallel implementations of the Space-Saving algorithm for
determining frequent items on a GPU. The first variant exploits the open-source CUB library …