Encyclopedia of Big Data Technologies

2019 Edition
| Editors: Sherif Sakr, Albert Y. Zomaya

Streaming Process Discovery and Conformance Checking

  • Andrea BurattinEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-3-319-77525-8_103



Streaming process discovery, streaming conformance checking, and streaming process mining in general (also known as online process mining) are disciplines which analyze event streams to extract a process model or to assess their conformance with respect to a given reference model. The main characteristic of this family of techniques is to analyze events immediately as they are generated (instead of storing them in a log for late processing). This allows to drastically reduce the latency among phases of the BPM lifecycle (cf. Dumas et al. 2013), thus allowing faster process adaptations and better executions.


A possible characterization of process mining algorithms is based on how they consume event data. Specifically, most of the algorithms focus on a (static) event log; however, there are algorithms which focus on event streams. An event log is a finite sampling of activities...

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.DTU Compute, Software EngineeringTechnical University of Denmark2800 Kgs. LyngbyDenmark