BPM 2014 - The Automated Discovery �of Hybrid Processes

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Presentation on the automated discovery of Hybrid Processes, given at the 12th International Conference on Business Process Management (BPM2014).

Transcript of BPM 2014 - The Automated Discovery �of Hybrid Processes

  • 1. The Automated Discoveryof Hybrid ProcessesFabrizio M. MaggiUniversity of TartuTijs Slaats*IT University ofCopenhagenExformaticsHajo A. ReijersVU University ofAmsterdam

2. Overview Hybrid Process Models Discovering Hybrid Process Models Evaluation Future Work + Conclusion 3. Imperative Process Models 4. Imperative Process Models Flow-oriented Well-suited to rigid processes In a model with no flow nothing can happen Adding flow allows for additional possiblebehaviors Common in academia and industry 5. Declarative Process Models 6. Declarative Process Models Constraint-oriented Well-suited to flexible processes In an unconstrained model anything canhappen Adding constraints limits behavior Still a novelty in industry 7. Hybrid Process Models 8. Hybrid Process Models Different parts of the same processmay be more or less flexible. Modeling a flexible process imperatively,or a strict process declaratively, oftenleads to incomprehensible models. Mixing of paradigms on the sub-process level: Pockets of flexibility in workflow services [Sadiq et al.] Flexibility as a Service (FAAS) [Aalst et al.] 9. Process DiscoveryEventLogProcess Model 10. Process Discovery Current discovery techniques: Mining Petri-nets / Flowcharts Alpha miner, Heuristic Miner, ILP miner, Mining Declarative constraints Declare miner But what if the log contains both flexible and rigidparts? Imperative miners tend to blow-up on flexible logs Declarative miners will need to find many constraints tomodel the strict parts of the process and will often havetrouble finding all of them (resulting in processes with lowprecision) Solution: Hybrid Process Discovery! 11. Hybrid Process DiscoveryContextanalysisClustering(based oncontext analysis)Clustering(association rulemining)StandardProcessDiscoveryDeclareDiscoveryString EditDistance 12. Evaluation BPI Challenge 2012Results of Imperative Miners 13. Evaluation BPI Challenge 2012Result of Hybrid Miner 14. Evaluation BPI Challenge 2012Comparison of ResultsFitnessSize 15. Future Work Proper plugin for Prom. Visualization of resulting hybrid model. Further evaluation on real cases. Further refinement of the heuristics used inthe approach, for example the thresholdsused for determining if an event is structuredor unstructured. 16. Conclusion We offer the first automated approach fordiscovering hybrid process models. Using the approach on existing logs givesencouraging results: in particular for semi-structuredlogs the discovered modelsbecome more readable. Plenty of room for future work in an excitingnew angle on process mining.