IMPresseD: Outcome-Oriented Interactive Multi-Interest Process Pattern Discovery Tool

Mozhgan Vazifehdoostirani; Laura Genga; Xixi Lu; Remco M. Dijkman

IMPresseD: Outcome-Oriented Interactive Multi-Interest Process Pattern Discovery Tool

Mozhgan Vazifehdoostirani, Laura Genga, Xixi Lu, Remco M. Dijkman

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Process pattern discovery methods (PPDMs) have been developed with the primary goal of identifying patterns of interest to users. Existing PPDM approaches are predominantly unsupervised and tend to focus on a single dimension of interest, such as discovering frequent patterns. We present IMPresseD, an interactive tool for exploring process patterns leveraging a multi-dimensional notion of interest. IMPresseD is designed to identify patterns that align with complex analytical objectives, such as deriving process patterns that affect the process outcome. Incorporating an iterative and interactive approach, this tool collaborates with domain experts to enhance pattern discovery.

Original language	English
Title of host publication	Doctoral Consortium and Demo Track 2023 at the International Conference on Process Mining 2023
Subtitle of host publication	co-located with the 5th International Conference on Process Mining (ICPM 2023) : Rome, Italy, October 27, 2023
Editors	Jan Martijn E.M. van der Werf, Cristina Cabanillas, Francesco Leotta, Laura Genga
Publisher	CEUR-WS.org
Number of pages	5
Publication status	Published - 2023
Event	5th International Conference on Process Mining, ICPM 2023 - Rome, Italy Duration: 23 Oct 2023 → 27 Oct 2023

Publication series

Name	CEUR Workshop Proceedings
Volume	3648
ISSN (Electronic)	1613-0073

Conference

Conference	5th International Conference on Process Mining, ICPM 2023
Country/Territory	Italy
City	Rome
Period	23/10/23 → 27/10/23

Keywords

Process Pattern Discovery
Multi-interest Pattern Detection
Outcome-Oriented Process Patterns

Access to Document

https://ceur-ws.org/Vol-3648/paper_9073.pdfLicence: CC BY

Cite this

Vazifehdoostirani, M., Genga, L., Lu, X., & Dijkman, R. M. (2023). IMPresseD: Outcome-Oriented Interactive Multi-Interest Process Pattern Discovery Tool . In J. M. E. M. van der Werf, C. Cabanillas, F. Leotta, & L. Genga (Eds.), Doctoral Consortium and Demo Track 2023 at the International Conference on Process Mining 2023: co-located with the 5th International Conference on Process Mining (ICPM 2023) : Rome, Italy, October 27, 2023 (CEUR Workshop Proceedings; Vol. 3648). CEUR-WS.org. https://ceur-ws.org/Vol-3648/paper_9073.pdf

Vazifehdoostirani, Mozhgan ; Genga, Laura ; Lu, Xixi et al. / IMPresseD : Outcome-Oriented Interactive Multi-Interest Process Pattern Discovery Tool . Doctoral Consortium and Demo Track 2023 at the International Conference on Process Mining 2023: co-located with the 5th International Conference on Process Mining (ICPM 2023) : Rome, Italy, October 27, 2023. editor / Jan Martijn E.M. van der Werf ; Cristina Cabanillas ; Francesco Leotta ; Laura Genga. CEUR-WS.org, 2023. (CEUR Workshop Proceedings).

@inproceedings{b58b3b0489624b29937a8648b565bbc8,

title = "IMPresseD: Outcome-Oriented Interactive Multi-Interest Process Pattern Discovery Tool ",

abstract = "Process pattern discovery methods (PPDMs) have been developed with the primary goal of identifying patterns of interest to users. Existing PPDM approaches are predominantly unsupervised and tend to focus on a single dimension of interest, such as discovering frequent patterns. We present IMPresseD, an interactive tool for exploring process patterns leveraging a multi-dimensional notion of interest. IMPresseD is designed to identify patterns that align with complex analytical objectives, such as deriving process patterns that affect the process outcome. Incorporating an iterative and interactive approach, this tool collaborates with domain experts to enhance pattern discovery.",

keywords = "Process Pattern Discovery, Multi-interest Pattern Detection, Outcome-Oriented Process Patterns",

author = "Mozhgan Vazifehdoostirani and Laura Genga and Xixi Lu and Dijkman, {Remco M.}",

year = "2023",

language = "English",

series = "CEUR Workshop Proceedings",

publisher = "CEUR-WS.org",

editor = "{van der Werf}, {Jan Martijn E.M.} and Cristina Cabanillas and Francesco Leotta and Laura Genga",

booktitle = "Doctoral Consortium and Demo Track 2023 at the International Conference on Process Mining 2023",

note = "5th International Conference on Process Mining, ICPM 2023 ; Conference date: 23-10-2023 Through 27-10-2023",

}

Vazifehdoostirani, M , Genga, L, Lu, X & Dijkman, RM 2023, IMPresseD: Outcome-Oriented Interactive Multi-Interest Process Pattern Discovery Tool . in JMEM van der Werf, C Cabanillas, F Leotta & L Genga (eds), Doctoral Consortium and Demo Track 2023 at the International Conference on Process Mining 2023: co-located with the 5th International Conference on Process Mining (ICPM 2023) : Rome, Italy, October 27, 2023. CEUR Workshop Proceedings, vol. 3648, CEUR-WS.org, 5th International Conference on Process Mining, ICPM 2023, Rome, Italy, 23/10/23. <https://ceur-ws.org/Vol-3648/paper_9073.pdf>

IMPresseD: Outcome-Oriented Interactive Multi-Interest Process Pattern Discovery Tool . / Vazifehdoostirani, Mozhgan ; Genga, Laura; Lu, Xixi et al.
Doctoral Consortium and Demo Track 2023 at the International Conference on Process Mining 2023: co-located with the 5th International Conference on Process Mining (ICPM 2023) : Rome, Italy, October 27, 2023. ed. / Jan Martijn E.M. van der Werf; Cristina Cabanillas; Francesco Leotta; Laura Genga. CEUR-WS.org, 2023. (CEUR Workshop Proceedings; Vol. 3648).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - IMPresseD

T2 - 5th International Conference on Process Mining, ICPM 2023

AU - Vazifehdoostirani, Mozhgan

AU - Genga, Laura

AU - Lu, Xixi

AU - Dijkman, Remco M.

PY - 2023

Y1 - 2023

N2 - Process pattern discovery methods (PPDMs) have been developed with the primary goal of identifying patterns of interest to users. Existing PPDM approaches are predominantly unsupervised and tend to focus on a single dimension of interest, such as discovering frequent patterns. We present IMPresseD, an interactive tool for exploring process patterns leveraging a multi-dimensional notion of interest. IMPresseD is designed to identify patterns that align with complex analytical objectives, such as deriving process patterns that affect the process outcome. Incorporating an iterative and interactive approach, this tool collaborates with domain experts to enhance pattern discovery.

AB - Process pattern discovery methods (PPDMs) have been developed with the primary goal of identifying patterns of interest to users. Existing PPDM approaches are predominantly unsupervised and tend to focus on a single dimension of interest, such as discovering frequent patterns. We present IMPresseD, an interactive tool for exploring process patterns leveraging a multi-dimensional notion of interest. IMPresseD is designed to identify patterns that align with complex analytical objectives, such as deriving process patterns that affect the process outcome. Incorporating an iterative and interactive approach, this tool collaborates with domain experts to enhance pattern discovery.

KW - Process Pattern Discovery

KW - Multi-interest Pattern Detection

KW - Outcome-Oriented Process Patterns

UR - https://github.com/MozhganVD/InteractivePatternDetection

M3 - Conference contribution

T3 - CEUR Workshop Proceedings

BT - Doctoral Consortium and Demo Track 2023 at the International Conference on Process Mining 2023

A2 - van der Werf, Jan Martijn E.M.

A2 - Cabanillas, Cristina

A2 - Leotta, Francesco

A2 - Genga, Laura

PB - CEUR-WS.org

Y2 - 23 October 2023 through 27 October 2023

ER -

Vazifehdoostirani M , Genga L, Lu X, Dijkman RM. IMPresseD: Outcome-Oriented Interactive Multi-Interest Process Pattern Discovery Tool . In van der Werf JMEM, Cabanillas C, Leotta F, Genga L, editors, Doctoral Consortium and Demo Track 2023 at the International Conference on Process Mining 2023: co-located with the 5th International Conference on Process Mining (ICPM 2023) : Rome, Italy, October 27, 2023. CEUR-WS.org. 2023. (CEUR Workshop Proceedings).

IMPresseD: Outcome-Oriented Interactive Multi-Interest Process Pattern Discovery Tool

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