Abstract
Process mining is a data-driven technique aiming to provide novel insights and help organizations to improve their business processes. In this paper, we focus on the cooperative aspect of process mining, i.e., discovering networks of cooperating resources that together perform processes. We use online streams of events as an input rather than event logs, which are typically used in an off-line setting. We present the Online Cooperative Network (OCN) framework, which defines online cooperative resource network discovery in a generic way. A prototypical implementation of the framework is available in the open source process mining toolkit ProM. By means of an empirical evaluation we show the applicability of the framework in the streaming domain. The techniques presented operate in a real time fashion and are able to handle unlimited amounts of data. Moreover, the implementation allows to visualize network dynamics, which helps in gaining insights in changes in the execution of the underlying business process.
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Experiments are performed on four Dell PowerEdge R520, 2 x Intel Xeon E5-2407 v2 2.40 GHz, 8\(\,\times \,\)8 8 GB RDIMM machines running Ubuntu 14.04 LTS. Experiment source code is available at: https://svn.win.tue.nl/repos/prom/Packages/StreamSocialNetworks/Branches/publications/2016_coopis/. Raw experiment results are available at https://github.com/s-j-v-zelst/research/releases/download/final/2016_coopis_experiments.tar.gz.
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van Zelst, S.J., van Dongen, B.F., van der Aalst, W.M.P. (2016). Online Discovery of Cooperative Structures in Business Processes. In: Debruyne, C., et al. On the Move to Meaningful Internet Systems: OTM 2016 Conferences. OTM 2016. Lecture Notes in Computer Science(), vol 10033. Springer, Cham. https://doi.org/10.1007/978-3-319-48472-3_12
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