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

Institute for Data, Process and Knowledge Management (AE Sabou)

Publication: Chapter in book/Conference proceeding › Contribution to conference proceedings

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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.

Original language	English
Title of host publication	Proceedings of the ER Forum and Poster & Demos Session 2019
Editors	José Ignacio Panach, Renata S.S. Guizzardi, Daniela Barreiro Claro
Place of Publication	Salvador, Brazil
Publisher	CEUR Workshop Proceedings
Pages	108 - 112
Publication status	Published - 2019

Austrian Classification of Fields of Science and Technology (ÖFOS)

102022 Software development
102
102001 Artificial intelligence
102013 Human-computer interaction
502
502050 Business informatics

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ERDemo01Final published version, 647 KBLicence: CC BY

http://ceur-ws.org/Vol-2469/ERDemo01.pdfLicence: Unspecified

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University Library Catalogue

RISE_BPM
Di Ciccio, C. (Researcher) & Mendling, J. (Researcher)
1/05/15 → 30/04/19
Project: Research

Cite this

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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",

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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 (ed.), Proceedings of the ER Forum and Poster & Demos Session 2019. CEUR Workshop Proceedings, Salvador, Brazil, pp. 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. ed. / José Ignacio Panach, Renata S.S. Guizzardi, Daniela Barreiro Claro. Salvador, Brazil: CEUR Workshop Proceedings, 2019. p. 108 - 112.

Publication: Chapter in book/Conference proceeding › Contribution to conference proceedings

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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

Austrian Classification of Fields of Science and Technology (ÖFOS)

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