Abstract. A statistical technique is developed for estimating the support of itemsets on data streams, regardless of the size of the data stored. This technique, which is computati...
Pierre-Alain Laur, Jean-Emile Symphor, Richard Noc...
We present memory-efficient deterministic algorithms for constructing -nets and -approximations of streams of geometric data. Unlike probabilistic approaches, these deterministic...
Amitabha Bagchi, Amitabh Chaudhary, David Eppstein...
In this paper, we present an abstract framework for online approximation of time-series data that yields a unified set of algorithms for several popular models: data streams, amnes...
This paper presents an incremental and scalable learning algorithm in order to mine numeric, low dimensionality, high–cardinality, time–changing data streams. Within the Superv...
We consider the problem of finding duplicates in data streams. Duplicate detection in data streams is utilized in various applications including fraud detection. We develop a solu...