We consider pervasive computing applications that process and aggregate data-streams emanating from highly distributed data sources to produce a stream of updates that have an imp...
Clustering streaming data requires algorithms which are capable of updating clustering results for the incoming data. As data is constantly arriving, time for processing is limited...
Philipp Kranen, Ira Assent, Corinna Baldauf, Thoma...
Data mining has recently attracted attention as a set of efficient techniques that can discover patterns from huge data. More recent advancements in collecting massive evolving da...
There are many application classes where the users are flexible with respect to the output quality. At the same time, there are other constraints, such as the need for real-time ...
There has been much recent interest in on-line data mining. Existing mining algorithms designed for stored data are either not applicable or not effective on data streams, where r...