Andrea Burattin

Associate Professor
Technical University of Denmark


Data Streams in ProM 6: A single-node architecture

S. J. van Zelst, A. Burattin, B. van Dongen, H.M.W. Verbeek
Abstract

Process mining is an active field of research that primarily builds upon data mining and process model-driven analysis. Within the field, static data is typically used. The usage of dynamic and/or volatile data (i.e. real-time streaming data) is very limited. Current process mining techniques are in general not able to cope with challenges posed by real-time data. Hence new approaches that enable us to apply process mining on such data are an interesting new field of study. The ProM-framework that supports a variety of researchers and domain experts in the field has therefore been extended with support for data-streams. This paper gives an overview of the newly created extension that lays a foundation for integrating streaming environments with ProM. Additionally a case study is presented in which a real-life online data stream has been incorporated in a basic ProM-based analysis.

Paper Information and Files

In Online Proceedings of the BPM Demo Track 2014; Haifa, Israel; September, 10 2014; CEUR-WS.org 2014.

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