We consider the problem of maintaining aggregates over recent elements of a massive data stream. Motivated by applications involving network data, we consider asynchronous data str...
We consider the problem of continuously maintaining order sketches over data streams with a relative rank error guarantee . Novel space-efficient and one-scan randomised technique...
In this paper, we give a simple scheme for identifying approximate frequent items over a sliding window of size n. Our scheme is deterministic and does not make any assumption on ...
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...
Processing and extracting meaningful knowledge from count data is an important problem in data mining. The volume of data is increasing dramatically as the data is generated by da...