Real-time response is crucial in many business process scenarios, however, few tools support the online processing of Process Mining tasks. In this paper, we present Concept Drift in Event Stream Framework (CDESF), a tool focused on concept drift detection that also supports several online Process Mining tasks. CDESF highlights the process model evolution during the stream processing and alerts the detection of new drifts aided by an online clustering layer. This paper presents CDESF as a tool that is available for the community and process practitioners.
The CDESF toolkit: An introduction / D. Mora, P. Ceravolo, E. Damiani, G. Marques Tavares (CEUR WORKSHOP PROCEEDINGS). - In: ICPM 2020 Doctoral Consortium and Tool Demonstration Track / [a cura di] C. Di Ciccio, B. Depaire, J. De Weerdt, C. Di Francescomarino, J. Munoz-Gama. - [s.l] : CEUR-WS, 2020. - pp. 47-50 (( convegno ICPM Doctoral Consortium and Tool Demonstration Track 2020 co-located with the 2nd International Conference on Process Mining tenutosi a Padova nel 2020.
The CDESF toolkit: An introduction
P. Ceravolo;E. Damiani;G. Marques Tavares
2020
Abstract
Real-time response is crucial in many business process scenarios, however, few tools support the online processing of Process Mining tasks. In this paper, we present Concept Drift in Event Stream Framework (CDESF), a tool focused on concept drift detection that also supports several online Process Mining tasks. CDESF highlights the process model evolution during the stream processing and alerts the detection of new drifts aided by an online clustering layer. This paper presents CDESF as a tool that is available for the community and process practitioners.
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