Complex Event Processing in ProSyWis

Abstract: The goal of the research project ProSyWis is to support so-called knowledge workers in their daily business. Knowledge workers are assumed to work on dynamic cases, whose sequence of actions can hardly be foreseen in advance. In contrast to static business models, dynamic cases are continuously driven by exogenous business events (e.g. E-Mails, location-based events, workflow events) or social media events (e.g. Twitter or RSS feeds) as well as by context-based data, as for instance, from previously closed cases or additional case-based meta data (e.g. the liquidity of a client). The CEP engine ESPER has been adopted for gathering, correlating, and analyzing these events. Given the occurrence of an event, further subsequent actions can be invoked within the CEP engine, for instance, for executing cases or business processes in a workflow engine or for reporting events together with recommended actions in a user portal. Stochastic models like MEP (Markov Decisions Process! es) are used to predict optimal strategies for invoking those actions that achieve maximal benefit. In this presentation, a brief introduction is given to the ProSyWis project. Besides, research results from various master and bachelor theses are presented that have aimed at integrating the CEP engine into the ProSyWis software architecture. A prototype will be presented demonstrating the capabilities of such an engine. Current and future research topics will be addressed in the end of the presentation. Speaker Bio: Sascha Alda works as a Professor of Computer Science at the University of Applied Sciences in Bonn since 2010. His main areas of interests in both research and education are software engineering, and software architecture. Before his academic career, he worked for various IT companies in industry such as IBM and Accenture. Sascha Alda received his doctoral degree at the University of Bonn (2006) and obtained a diploma in Computer Science at the University of Koblenz (2000).

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