Name
Abstract | ||
|---|---|---|
Complex Event Processing handles processing of a large number of heterogeneous events and pattern detection over multiple event streams in real-time. Situations of interests are modeled using event patterns which describe a specific situation in an event processing language. In order to leverage the usage of event processing in everyday situations, a clear methodology for the identification and definition of events and event patterns is needed. In this paper, we propose an end-to-end methodology for designing event processing systems. This methodology integrates domain knowledge modeled during the setup phase of event processing with a high-level event pattern language which allows users to create specific business-related patterns. In addition, our methodology regards the circumstance that some patterns might have to be defined by technical experts and therefore introduces an actor model. Our approach is validated based on a real use case of a supplier of convenience stores. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-38709-8_9 | CA(i)SE |
Keywords | Field | DocType |
clear methodology,multiple event stream,fast data processing,high-level event pattern language,event processing language,event pattern,end-to-end methodology,event processing,heterogeneous event,pattern detection,event processing system | Customer relationship management,Data mining,Data processing,Enterprise architecture,Domain knowledge,Computer science,Complex event processing,Pattern language,Event tree analysis,Actor model | Conference |
Citations | PageRank | References |
2 | 0.51 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dominik Riemer | 1 | 12 | 5.23 |
| Nenad Stojanovic | 2 | 1605 | 152.52 |
| Ljiljana Stojanovic | 3 | 1113 | 119.17 |