Aggregating Event Knowledge Graphs for Task Analysis

Eva L. Klijn; Felix Mannhardt; Dirk Fahland

doi:10.1007/978-3-031-27815-0_36

Aggregating Event Knowledge Graphs for Task Analysis

Eva L. Klijn, Felix Mannhardt, Dirk Fahland

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

Abstract

Aggregation of event data is a key operation in process mining for revealing behavioral features of processes for analysis. It has primarily been studied over sequences of events in event logs. The data model of event knowledge graphs enables new analysis questions requiring new forms of aggregation. We focus on analyzing task executions in event knowledge graphs. We show that existing aggregation operations are inadequate and propose new aggregation operations, formulated as query operators over labeled property graphs. We show on the BPIC’17 dataset that the new aggregation operations allow gaining new insights into differences in task executions, actor behavior, and work division.

Original language	English
Title of host publication	Process Mining Workshops - ICPM 2022 International Workshops, Revised Selected Papers
Editors	Marco Montali, Arik Senderovich, Matthias Weidlich
Publisher	Springer
Pages	493-505
Number of pages	13
ISBN (Print)	9783031278143
DOIs	https://doi.org/10.1007/978-3-031-27815-0_36
Publication status	Published - 2023
Event	International Workshops on EDBA, ML4PM, RPM, PODS4H, SA4PM, PQMI, EduPM, and DQT-PM, held at the International Conference on Process Mining, ICPM 2022 - Bozen-Bolzano, Italy Duration: 23 Oct 2022 → 28 Oct 2022

Publication series

Name	Lecture Notes in Business Information Processing
Volume	468 LNBIP
ISSN (Print)	1865-1348
ISSN (Electronic)	1865-1356

Conference

Conference	International Workshops on EDBA, ML4PM, RPM, PODS4H, SA4PM, PQMI, EduPM, and DQT-PM, held at the International Conference on Process Mining, ICPM 2022
Country/Territory	Italy
City	Bozen-Bolzano
Period	23/10/22 → 28/10/22

Bibliographical note

Publisher Copyright:
© 2023, The Author(s).

Keywords

Aggregation
Knowledge graph
Tasks

Access to Document

10.1007/978-3-031-27815-0_36

Cite this

Klijn, E. L., Mannhardt, F., & Fahland, D. (2023). Aggregating Event Knowledge Graphs for Task Analysis. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops - ICPM 2022 International Workshops, Revised Selected Papers (pp. 493-505). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). Springer. https://doi.org/10.1007/978-3-031-27815-0_36

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Klijn, EL , Mannhardt, F & Fahland, D 2023, Aggregating Event Knowledge Graphs for Task Analysis. in M Montali, A Senderovich & M Weidlich (eds), Process Mining Workshops - ICPM 2022 International Workshops, Revised Selected Papers. Lecture Notes in Business Information Processing, vol. 468 LNBIP, Springer, pp. 493-505, International Workshops on EDBA, ML4PM, RPM, PODS4H, SA4PM, PQMI, EduPM, and DQT-PM, held at the International Conference on Process Mining, ICPM 2022, Bozen-Bolzano, Italy, 23/10/22. https://doi.org/10.1007/978-3-031-27815-0_36

Aggregating Event Knowledge Graphs for Task Analysis. / Klijn, Eva L.; Mannhardt, Felix ; Fahland, Dirk.
Process Mining Workshops - ICPM 2022 International Workshops, Revised Selected Papers. ed. / Marco Montali; Arik Senderovich; Matthias Weidlich. Springer, 2023. p. 493-505 (Lecture Notes in Business Information Processing; Vol. 468 LNBIP).

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

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