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.