Comprehensive Process Drift Analysis with the Visual Drift Detection Tool

Anton Yeshchenko; Claudio Di Ciccio; Jan Mendling; Artem Polyvyanyy

Comprehensive Process Drift Analysis with the Visual Drift Detection Tool

Anton Yeshchenko, Claudio Di Ciccio, Jan Mendling, Artem Polyvyanyy

Data, Process and Knowledge Management (Sabou)

Publikation: Beitrag in Buch/Konferenzband › Beitrag in Konferenzband

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Abstract

Recent research has introduced ideas from concept drift into process mining to enable the analysis of changes in business processes over time. This stream of research, however, has not yet addressed the challenges of drift categorization, drilling-down, and quantification. In this tool demonstration paper, we present a novel software tool to analyze process drifts, called Visual Drift Detection (VDD), which fulfills these requirements. The tool is of benefit to the researchers and practitioners in the business intelligence and process analytics area, and can constitute a valuable aid to those who are involved in business process redesign endeavors.

Originalsprache	Englisch
Titel des Sammelwerks	Proceedings of the ER Forum and Poster & Demos Session 2019
Herausgeber*innen	José Ignacio Panach, Renata S.S. Guizzardi, Daniela Barreiro Claro
Erscheinungsort	Salvador, Brazil
Verlag	CEUR Workshop Proceedings
Seiten	108 - 112
Publikationsstatus	Veröffentlicht - 2019

Österreichische Systematik der Wissenschaftszweige (ÖFOS)

102022 Softwareentwicklung
102
102001 Artificial Intelligence
102013 Human-Computer Interaction
502
502050 Wirtschaftsinformatik

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ERDemo01Endgültige, publizierte Fassung, 647 KBLizenz: CC BY

http://ceur-ws.org/Vol-2469/ERDemo01.pdfLizenz: Nicht angegeben

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RISE_BPM
Di Ciccio, C. (Forscher*in) & Mendling, J. (Forscher*in)
1/05/15 → 30/04/19
Projekt: Forschung

Zitat

@inproceedings{8197b5d37b3441b99ac11ae64542ec19,

title = "Comprehensive Process Drift Analysis with the Visual Drift Detection Tool",

abstract = "Recent research has introduced ideas from concept drift into process mining to enable the analysis of changes in business processes over time. This stream of research, however, has not yet addressed the challenges of drift categorization, drilling-down, and quantification. In this tool demonstration paper, we present a novel software tool to analyze process drifts, called Visual Drift Detection (VDD), which fulfills these requirements. The tool is of benefit to the researchers and practitioners in the business intelligence and process analytics area, and can constitute a valuable aid to those who are involved in business process redesign endeavors.",

author = "Anton Yeshchenko and {Di Ciccio}, Claudio and Jan Mendling and Artem Polyvyanyy",

year = "2019",

language = "English",

pages = "108 -- 112",

editor = "{Jos{\'e} Ignacio Panach, Renata S.S. Guizzardi, Daniela Barreiro Claro}",

booktitle = "Proceedings of the ER Forum and Poster & Demos Session 2019",

publisher = "CEUR Workshop Proceedings",

}

Yeshchenko, A, Di Ciccio, C, Mendling, J & Polyvyanyy, A 2019, Comprehensive Process Drift Analysis with the Visual Drift Detection Tool. in José Ignacio Panach, Renata S.S. Guizzardi, Daniela Barreiro Claro (Hrsg.), Proceedings of the ER Forum and Poster & Demos Session 2019. CEUR Workshop Proceedings, Salvador, Brazil, S. 108 - 112. <http://ceur-ws.org/Vol-2469/ERDemo01.pdf>

Comprehensive Process Drift Analysis with the Visual Drift Detection Tool. / Yeshchenko, Anton; Di Ciccio, Claudio; Mendling, Jan et al.
Proceedings of the ER Forum and Poster & Demos Session 2019. Hrsg. / José Ignacio Panach, Renata S.S. Guizzardi, Daniela Barreiro Claro. Salvador, Brazil: CEUR Workshop Proceedings, 2019. S. 108 - 112.

Publikation: Beitrag in Buch/Konferenzband › Beitrag in Konferenzband

TY - GEN

T1 - Comprehensive Process Drift Analysis with the Visual Drift Detection Tool

AU - Yeshchenko, Anton

AU - Di Ciccio, Claudio

AU - Mendling, Jan

AU - Polyvyanyy, Artem

PY - 2019

Y1 - 2019

N2 - Recent research has introduced ideas from concept drift into process mining to enable the analysis of changes in business processes over time. This stream of research, however, has not yet addressed the challenges of drift categorization, drilling-down, and quantification. In this tool demonstration paper, we present a novel software tool to analyze process drifts, called Visual Drift Detection (VDD), which fulfills these requirements. The tool is of benefit to the researchers and practitioners in the business intelligence and process analytics area, and can constitute a valuable aid to those who are involved in business process redesign endeavors.

AB - Recent research has introduced ideas from concept drift into process mining to enable the analysis of changes in business processes over time. This stream of research, however, has not yet addressed the challenges of drift categorization, drilling-down, and quantification. In this tool demonstration paper, we present a novel software tool to analyze process drifts, called Visual Drift Detection (VDD), which fulfills these requirements. The tool is of benefit to the researchers and practitioners in the business intelligence and process analytics area, and can constitute a valuable aid to those who are involved in business process redesign endeavors.

M3 - Contribution to conference proceedings

SP - 108

EP - 112

BT - Proceedings of the ER Forum and Poster & Demos Session 2019

A2 - José Ignacio Panach, Renata S.S. Guizzardi, Daniela Barreiro Claro, null

PB - CEUR Workshop Proceedings

CY - Salvador, Brazil

ER -

Comprehensive Process Drift Analysis with the Visual Drift Detection Tool

Abstract

Österreichische Systematik der Wissenschaftszweige (ÖFOS)

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