Stream Event Detection: A Unified Framework for Mining Outlier, Change and Burst Simultaneously over Data Stream

Event detection is one of the most important issues of event processing system, especially Complex Event Processing (CEP). Outlier event, change event and burst event are three typical types of event that need to be identified. Current research works always deal with only one kind of event and can not detect various types of event simultaneously. We address how to detect multiple types of event from data stream simultaneously in one framework. In this paper, we first explore the relationship of these three types of events, and then present a unified method for dealing with all of them. In order to evaluate the event, several score functions are defined for each type of event as well. Simulation results testify the efficiency of the proposed framework.