Predictive Complex Event Processing: A conceptual framework for combining Complex Event Processing and Predictive Analytics

Lajos Jenő Fülöp, Gabriella Tóth, László Vidács, Árpád Beszédes, Hunor Demeter, Lóránt Farkas, Tibor Gyimóthy and Gergő Balogh
Complex Event Processing deals with the detection of complex events based on rules and patterns defined by domain experts. Many complex events require real-time detection in order to have enough time for appropriate reactions. However, there are several events (e.g. credit card fraud) that should be prevented proactively before they occur, not just responded after they happened. In this paper, we briefly describe Complex Event Processing (CEP) and Predictive Analytics (PA). Afterwards, we focus on a major future direction of CEP, namely the inclusion of PA technologies into CEP tools and applications. Involving PA opens a wide range of possibilities in several application fields. However, we have observed that only few solutions apply PA techniques. In this paper, we define a conceptual framework which combines CEP and PA and which can be the basis of generic design pattern in the future. The conceptual framework is demonstrated in a proof-of-concept experiment. Finally we provide the results and lessons learned.

Keywords: CEP, Complex event processing, predictive analytics.