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...
Abstract-- Our demonstration introduces a novel system architecture which massively facilitates optimization in data stream management systems (DSMS). The basic idea is to decouple...
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...
Outlyingness is a subjective concept relying on the isolation level of a (set of) record(s). Clustering-based outlier detection is a field that aims to cluster data and to detect...
In this demo, we present Nile-PDT, a Phenomenon Detection and Tracking framework using the Nile data stream management system. A phenomenon is characterized by a group of streams ...
Mohamed H. Ali, Walid G. Aref, Raja Bose, Ahmed K....