In this paper, we will examine the problem of clustering massive domain data streams. Massive-domain data streams are those in which the number of possible domain values for each a...
Applications that monitor functions over rapidly and unpredictably changing data, express their needs as continuous queries. Our focus is on a rich class of queries, expressed as p...
Data streams are often locally correlated, with a subset of streams exhibiting coherent patterns over a subset of time points. Subspace clustering can discover clusters of objects...
We study the problem of maintaining sketches of recent elements of a data stream. Motivated by applications involving network data, we consider streams that are asynchronous, in w...
On-line decision making often involves query processing over time-varying data which arrives in the form of data streams from distributed locations. In such environments typically...