The recent advances in hardware and software have enabled the capture of different measurements of data in a wide range of fields. These measurements are generated continuously an...
Mohamed Medhat Gaber, Arkady B. Zaslavsky, Shonali...
This paper gives an overview of recent work on machine models for processing massive amounts of data. The main focus is on generalizations of the classical data stream model where...
In the past years, the theory and practice of machine learning and data mining have been focused on static and finite data sets from where learning algorithms generate a static m...
The two main challenges typically associated with mining data streams are concept drift and data contamination. To address these challenges, we seek learning techniques and models ...
We consider the problem of approximating sliding window joins over data streams in a data stream processing system with limited resources. In our model, we deal with resource cons...