Detecting change in processes using comparative trace clustering

B.F.A. Hompes, J.C.A.M. Buijs, W.M.P. van der Aalst, P.M. Dixit, J. Buurman

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

8 Citaties (Scopus)

Uittreksel

Real-life business processes are complex and show a high degree of variability. Additionally, due to changing conditions and circumstances, these processes continuously evolve over time. For example, in the healthcare domain, advances in medicine trigger changes in diagnoses and treatment processes. Besides changes over time, case data (e.g. treating physician, patient age) also influence how processes are executed. Existing process mining techniques assume processes to be static and therefore are less suited for the analysis of contemporary flexible business processes. This paper presents a novel comparative trace clustering approach that is able to expose changes in behavior. Valuable insights can be gained and process improvements can be made by finding those points in time where behavior changed and the reasons why. Evaluation on real-life event data shows our technique can provide these insights.

TaalEngels
TitelProceedings of the 5th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2015), Vienna, Austria, December 9-11, 2015
RedacteurenP. Caravolo, S. Rinderle-Ma
UitgeverijCEUR-WS.org
Pagina's95-108
Aantal pagina's14
StatusGepubliceerd - 2015
Evenement5th International Symposium on Data-Driven Process Discovery and Analysis (SIMPDA 2015 - Vienna, Oostenrijk
Duur: 9 dec 201511 dec 2015
Congresnummer: 5

Publicatie series

NaamCEUR Workshop Proceedings
UitgeverijCEUR
Volume1527
ISSN van geprinte versie1613-0073

Congres

Congres5th International Symposium on Data-Driven Process Discovery and Analysis (SIMPDA 2015
Verkorte titelSIMPDA 2015
LandOostenrijk
StadVienna
Periode9/12/1511/12/15

Vingerafdruk

Medicine
Industry

Trefwoorden

    Citeer dit

    Hompes, B. F. A., Buijs, J. C. A. M., van der Aalst, W. M. P., Dixit, P. M., & Buurman, J. (2015). Detecting change in processes using comparative trace clustering. In P. Caravolo, & S. Rinderle-Ma (editors), Proceedings of the 5th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2015), Vienna, Austria, December 9-11, 2015 (blz. 95-108). (CEUR Workshop Proceedings; Vol. 1527). CEUR-WS.org.
    Hompes, B.F.A. ; Buijs, J.C.A.M. ; van der Aalst, W.M.P. ; Dixit, P.M. ; Buurman, J./ Detecting change in processes using comparative trace clustering. Proceedings of the 5th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2015), Vienna, Austria, December 9-11, 2015. redacteur / P. Caravolo ; S. Rinderle-Ma. CEUR-WS.org, 2015. blz. 95-108 (CEUR Workshop Proceedings).
    @inproceedings{fe250f72aa6a47b8844b9a3dca2a3904,
    title = "Detecting change in processes using comparative trace clustering",
    abstract = "Real-life business processes are complex and show a high degree of variability. Additionally, due to changing conditions and circumstances, these processes continuously evolve over time. For example, in the healthcare domain, advances in medicine trigger changes in diagnoses and treatment processes. Besides changes over time, case data (e.g. treating physician, patient age) also influence how processes are executed. Existing process mining techniques assume processes to be static and therefore are less suited for the analysis of contemporary flexible business processes. This paper presents a novel comparative trace clustering approach that is able to expose changes in behavior. Valuable insights can be gained and process improvements can be made by finding those points in time where behavior changed and the reasons why. Evaluation on real-life event data shows our technique can provide these insights.",
    keywords = "Concept Drift, Process Comparison, Process mining, Trace Clustering",
    author = "B.F.A. Hompes and J.C.A.M. Buijs and {van der Aalst}, W.M.P. and P.M. Dixit and J. Buurman",
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    Hompes, BFA, Buijs, JCAM, van der Aalst, WMP, Dixit, PM & Buurman, J 2015, Detecting change in processes using comparative trace clustering. in P Caravolo & S Rinderle-Ma (redactie), Proceedings of the 5th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2015), Vienna, Austria, December 9-11, 2015. CEUR Workshop Proceedings, vol. 1527, CEUR-WS.org, blz. 95-108, Vienna, Oostenrijk, 9/12/15.

    Detecting change in processes using comparative trace clustering. / Hompes, B.F.A.; Buijs, J.C.A.M.; van der Aalst, W.M.P.; Dixit, P.M.; Buurman, J.

    Proceedings of the 5th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2015), Vienna, Austria, December 9-11, 2015. redactie / P. Caravolo; S. Rinderle-Ma. CEUR-WS.org, 2015. blz. 95-108 (CEUR Workshop Proceedings; Vol. 1527).

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

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    T1 - Detecting change in processes using comparative trace clustering

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    AU - Buijs,J.C.A.M.

    AU - van der Aalst,W.M.P.

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    AB - Real-life business processes are complex and show a high degree of variability. Additionally, due to changing conditions and circumstances, these processes continuously evolve over time. For example, in the healthcare domain, advances in medicine trigger changes in diagnoses and treatment processes. Besides changes over time, case data (e.g. treating physician, patient age) also influence how processes are executed. Existing process mining techniques assume processes to be static and therefore are less suited for the analysis of contemporary flexible business processes. This paper presents a novel comparative trace clustering approach that is able to expose changes in behavior. Valuable insights can be gained and process improvements can be made by finding those points in time where behavior changed and the reasons why. Evaluation on real-life event data shows our technique can provide these insights.

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    Hompes BFA, Buijs JCAM, van der Aalst WMP, Dixit PM, Buurman J. Detecting change in processes using comparative trace clustering. In Caravolo P, Rinderle-Ma S, redacteurs, Proceedings of the 5th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2015), Vienna, Austria, December 9-11, 2015. CEUR-WS.org. 2015. blz. 95-108. (CEUR Workshop Proceedings).