Continuously matching episode rules for predicting future events over event streams

Abstract

Predicting future events has great importance in many applications. Generally, rules with predicate events and consequent events are mined out, and then current events are matched with the predicate ones to predict the occurrence of consequent events. Many previous works focus on the rule mining problem; however, little emphasis has been attached to the problem of predicate events matching. As events often arrive in a stream, how to design an efficient and effective event predictor becomes challenging. In this paper, we give a clear definition of this problem and propose our own method. We develop an event filter and incrementally maintain parts of the matching results. By running a series of experiments, we show that our method is efficient and effective in the stream environment. © Springer-Verlag Berlin Heidelberg 2007.