Abstract
Event prediction over event streams is an important problem with broad applications. For this problem, rules with predicate events and consequent events are given, and then current events are matched with the predicate events to predict future events. Over the event stream, some matches of predicate events may trigger duplicate predictions, and an effective scheme is proposed to avoid such redundancies. Based on the scheme, we propose a novel approach CBS-Tree to efficiently match the predicate events over event streams. The CBS-Tree approach maintains the recently arrived events as a tree structure, and an efficient algorithm is proposed for the matching of predicate events on the tree structure, which avoids exhaustive scans of the arrived events. By running a series of experiments, we show that our approach is more efficient than the previous work for most cases.
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Cho, CW., Zheng, Y., Wu, YH., Chen, A.L.P. (2008). A Tree-Based Approach for Event Prediction Using Episode Rules over Event Streams. In: Bhowmick, S.S., Küng, J., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2008. Lecture Notes in Computer Science, vol 5181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85654-2_24
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DOI: https://doi.org/10.1007/978-3-540-85654-2_24
Publisher Name: Springer, Berlin, Heidelberg
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