A major problem in detecting events in streams of data is that the data can be imprecise (e.g. RFID data). However, current state-ofthe-art event detection systems such as Cayuga ...
A burst is a large number of events occurring within a certain time window. As an unusual activity, it's a noteworthy phenomenon in many natural and social processes. Many da...
We introduce the new paradigm of Change Mining as data mining over a volatile, evolving world with the objective of understanding change. While there is much work on incremental m...
We present a new pointer analysis for use in shared memory programs running on hierarchical parallel machines. The analysis is motivated by the partitioned global address space lan...
Abstract. E cient data mining algorithms are crucial fore ective knowledge discovery. We present the Multi-Stream Dependency Detection (msdd) data mining algorithm that performs a ...