Enhancing process mining results using domain knowledge

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

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademic

2 Citaties (Scopus)

Uittreksel

Process discovery algorithms typically aim at discovering process models from event logs. Most discovery algorithms discover the model based on an event log, without allowing the domain expert to influence the discovery approach in any way. However, the user may have certain domain expertise which should be exploited to create a better process model. In this paper, we address this issue of incorporating domain knowledge to improve the discovered process model. We firstly present a modification algorithm to modify a discovered process model. Furthermore, we present a verification algorithm to verify the presence of user specified constraints in the model. The outcome of our approach is a Pareto front of process models based on the constraints specified by the domain expert and common quality dimensions of process mining.

TaalEngels
TitelInternational Symposium on Data-driven Process Discovery and Analysis 2015, Vienna, Austria.
RedacteurenP. Caravolo, S. Rinderle-Ma
UitgeverijCEUR-WS.org
Pagina's79-94
Aantal pagina's16
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

Trefwoorden

    Citeer dit

    Dixit, P. M., Buijs, J. C. A. M., van der Aalst, W. M. P., Hompes, B. F. A., & Buurman, J. (2015). Enhancing process mining results using domain knowledge. In P. Caravolo, & S. Rinderle-Ma (editors), International Symposium on Data-driven Process Discovery and Analysis 2015, Vienna, Austria. (blz. 79-94). (CEUR Workshop Proceedings; Vol. 1527). CEUR-WS.org.
    Dixit, P.M. ; Buijs, J.C.A.M. ; van der Aalst, W.M.P. ; Hompes, B.F.A. ; Buurman, J./ Enhancing process mining results using domain knowledge. International Symposium on Data-driven Process Discovery and Analysis 2015, Vienna, Austria. . redacteur / P. Caravolo ; S. Rinderle-Ma. CEUR-WS.org, 2015. blz. 79-94 (CEUR Workshop Proceedings).
    @inproceedings{694d30a6c5bc4ad799763bcdd4cacac0,
    title = "Enhancing process mining results using domain knowledge",
    abstract = "Process discovery algorithms typically aim at discovering process models from event logs. Most discovery algorithms discover the model based on an event log, without allowing the domain expert to influence the discovery approach in any way. However, the user may have certain domain expertise which should be exploited to create a better process model. In this paper, we address this issue of incorporating domain knowledge to improve the discovered process model. We firstly present a modification algorithm to modify a discovered process model. Furthermore, we present a verification algorithm to verify the presence of user specified constraints in the model. The outcome of our approach is a Pareto front of process models based on the constraints specified by the domain expert and common quality dimensions of process mining.",
    keywords = "Algorithm Post Processing, Declare Templates, Domain Knowledge, User Guided Process Discovery",
    author = "P.M. Dixit and J.C.A.M. Buijs and {van der Aalst}, W.M.P. and B.F.A. Hompes and J. Buurman",
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    }

    Dixit, PM, Buijs, JCAM, van der Aalst, WMP, Hompes, BFA & Buurman, J 2015, Enhancing process mining results using domain knowledge. in P Caravolo & S Rinderle-Ma (redactie), International Symposium on Data-driven Process Discovery and Analysis 2015, Vienna, Austria. . CEUR Workshop Proceedings, vol. 1527, CEUR-WS.org, blz. 79-94, Vienna, Oostenrijk, 9/12/15.

    Enhancing process mining results using domain knowledge. / Dixit, P.M.; Buijs, J.C.A.M.; van der Aalst, W.M.P.; Hompes, B.F.A.; Buurman, J.

    International Symposium on Data-driven Process Discovery and Analysis 2015, Vienna, Austria. . redactie / P. Caravolo; S. Rinderle-Ma. CEUR-WS.org, 2015. blz. 79-94 (CEUR Workshop Proceedings; Vol. 1527).

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    AB - Process discovery algorithms typically aim at discovering process models from event logs. Most discovery algorithms discover the model based on an event log, without allowing the domain expert to influence the discovery approach in any way. However, the user may have certain domain expertise which should be exploited to create a better process model. In this paper, we address this issue of incorporating domain knowledge to improve the discovered process model. We firstly present a modification algorithm to modify a discovered process model. Furthermore, we present a verification algorithm to verify the presence of user specified constraints in the model. The outcome of our approach is a Pareto front of process models based on the constraints specified by the domain expert and common quality dimensions of process mining.

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    Dixit PM, Buijs JCAM, van der Aalst WMP, Hompes BFA, Buurman J. Enhancing process mining results using domain knowledge. In Caravolo P, Rinderle-Ma S, redacteurs, International Symposium on Data-driven Process Discovery and Analysis 2015, Vienna, Austria. . CEUR-WS.org. 2015. blz. 79-94. (CEUR Workshop Proceedings).