TY - JOUR
T1 - The CDESF toolkit
T2 - 2020 ICPM Doctoral Consortium and Tool Demonstration Track, ICPM-D 2020
AU - Mora, Davide
AU - Ceravolo, Paolo
AU - Damiani, Ernesto
AU - Tavares, Gabriel Marques
N1 - Funding Information:
This study was also partly supported by the program “Piano di sostegno alla ricerca 2019” funded by Università degli Studi di Milano.
Publisher Copyright:
© 2020 CEUR-WS. All rights reserved.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Clustering
KW - Concept drift detection
KW - Online process mining
KW - Process model graph
UR - https://www.scopus.com/pages/publications/85094864286
M3 - Conference article
AN - SCOPUS:85094864286
SN - 1613-0073
VL - 2703
SP - 47
EP - 50
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
Y2 - 4 October 2020 through 9 October 2020
ER -