This paper introduces the Dynamic Cascade Tree (DCT), a structure designed to index query regions on multi-dimensional data streams. The DCT is designed for a stream management sy...
We introduce a new sublinear space data structure—the Count-Min Sketch— for summarizing data streams. Our sketch allows fundamental queries in data stream summarization such a...
Data streams are a prevalent and growing source of timely data. As streams become more prevalent, richer interrogation of the contents of the streams are required. Value of the con...
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 ...
The problem of estimating the kth frequency moment Fk for any nonnegative k, over a data stream by looking at the items exactly once as they arrive, was considered in a seminal pap...
Emerging data stream management systems approach the challenge of massive data distributions which arrive at high speeds while there is only small storage by summarizing and minin...
In this demo, we show that intelligent load shedding is essential in achieving optimum results in mining data streams under various resource constraints. The Loadstar system intro...
Abstract. The data stream model of computation is often used for analyzing huge volumes of continuously arriving data. In this paper, we present a novel algorithm called DUCstream ...
We present novel algorithms for estimating the size of the natural join of two data streams that have efficient update processing times and provide excellent quality of estimates....
Histograms are used in many ways in conventional databases and in data stream processing for summarizing massive data distributions. Previous work on constructing histograms on da...