—“Big Data” in map-reduce (M-R) clusters is often fundamentally temporal in nature, as are many analytics tasks over such data. For instance, display advertising uses Behavio...
Badrish Chandramouli, Jonathan Goldstein, Songyun ...
The major challenge in mining data streams is the issue of concept drift, the tendency of the underlying data generation process to change over time. In this paper, we propose a g...
Provenance becomes a critical requirement for healthcare IT infrastructures, especially when pervasive biomedical sensors act as a source of raw medical streams for large-scale, a...
Min Wang, Marion Blount, John Davis, Archan Misra,...
Abstract—We present an efficient and robust stepping-stone detection scheme based on succinct packet-timing sketches of network flows. The proposed scheme employs an online alg...
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan