The CDESF toolkit: An introduction

Davide Mora; Paolo Ceravolo; Ernesto Damiani; Gabriel Marques Tavares

The CDESF toolkit: An introduction

Davide Mora
, Paolo Ceravolo
, Ernesto Damiani
, Gabriel Marques Tavares

Electrical Engineering

Università degli Studi di Milano

Research output: Contribution to journal › Conference article › peer-review

5 Scopus citations

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.

Original language	British English
Pages (from-to)	47-50
Number of pages	4
Journal	CEUR Workshop Proceedings
Volume	2703
State	Published - 2020
Event	2020 ICPM Doctoral Consortium and Tool Demonstration Track, ICPM-D 2020 - Padua, Italy Duration: 4 Oct 2020 → 9 Oct 2020

Keywords

Clustering
Concept drift detection
Online process mining
Process model graph

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title = "The CDESF toolkit: An introduction",

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.",

keywords = "Clustering, Concept drift detection, Online process mining, Process model graph",

author = "Davide Mora and Paolo Ceravolo and Ernesto Damiani and Tavares, \{Gabriel Marques\}",

note = "Funding Information: This study was also partly supported by the program “Piano di sostegno alla ricerca 2019” funded by Universit{\`a} degli Studi di Milano. Publisher Copyright: {\textcopyright} 2020 CEUR-WS. All rights reserved.; 2020 ICPM Doctoral Consortium and Tool Demonstration Track, ICPM-D 2020 ; Conference date: 04-10-2020 Through 09-10-2020",

year = "2020",

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journal = "CEUR Workshop Proceedings",

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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 -

The CDESF toolkit: An introduction

Abstract

Keywords

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