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 ...
In a massive stream of sequential events such as stock feeds, sensor readings, or IP traffic measurements, tuples pertaining to recent events are typically more important than olde...
Similarity search in time series databases is an important research direction. Several methods have been proposed in order to provide algorithms for efficient query processing in t...
Maria Kontaki, Apostolos Papadopoulos, Yannis Mano...
We propose two new data stream models: the reset model and the delta model, motivated by applications to databases, and to tracking the location of spatial points. We present algor...
Michael Hoffmann 0002, S. Muthukrishnan, Rajeev Ra...
There is a growing interest in on-line algorithms for analyzing and querying data streams, that examine each stream element only once and have at their disposal, only a limited amo...
Sumit Ganguly, Minos N. Garofalakis, Rajeev Rastog...