Online monitoring of data streams poses a challenge in many data-centric applications, such as telecommunications networks, traffic management, trend-related analysis, webclick st...
Approximating pairwise, or k-wise, independence with sublinear memory is of considerable importance in the data stream model. In the streaming model the joint distribution is give...
Incremental pattern discovery targets streaming applications where the data continuously arrive incrementally. The questions are how to find patterns (main trends) incrementally; ...
We consider the problem of pipelined filters, where a continuous stream of tuples is processed by a set of commutative filters. Pipelined filters are common in stream applications...
In this paper, we introduce SPIRIT (Streaming Pattern dIscoveRy in multIple Timeseries). Given n numerical data streams, all of whose values we observe at each time tick t, SPIRIT...