Complex queries over high speed data streams often need to rely on approximations to keep up with their input. The research community has developed a rich literature on approximat...
Theodore Johnson, S. Muthukrishnan, Irina Rozenbau...
We present a fast algorithm for computing approximate quantiles in high speed data streams with deterministic error bounds. For data streams of size N where N is unknown in advanc...
Sequential pattern mining is an active field in the domain of knowledge discovery. Recently, with the constant progress in hardware technologies, real-world databases tend to gro...
A fundamental problem in data management is to draw a sample of a large data set, for approximate query answering, selectivity estimation, and query planning. With large, streamin...
Graham Cormode, S. Muthukrishnan, Ke Yi, Qin Zhang
Uncertain data streams, where data is incomplete, imprecise, and even misleading, have been observed in many environments. Feeding such data streams to existing stream systems pro...
Thanh T. L. Tran, Liping Peng, Boduo Li, Yanlei Di...