Abstract
Information systems have been widely adopted to support service processes in various domains, e.g., in the telecommunication, finance, and health sectors. Recently, work on process mining showed how management of these processes, and engineering of supporting systems, can be guided by models extracted from the event logs that are recorded during process operation. In this work, we establish a queueing perspective in operational process mining. We propose to consider queues as first-class citizens and use queueing theory as a basis for queue mining techniques. To demonstrate the value of queue mining, we revisit the specific operational problem of online delay prediction: using event data, we show that queue mining yields accurate online predictions of case delay.
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References
van der Aalst, W.M.P., Weijters, T., Maruster, L.: Workflow mining: Discovering process models from event logs. IEEE Trans. Knowl. Data Eng. 16(9), 1128–1142 (2004)
van der Aalst, W.M.P.: Workflow verification: Finding control-flow errors using petri-net-based techniques. In: van der Aalst, W.M.P., Desel, J., Oberweis, A. (eds.) Business Process Management. LNCS, vol. 1806, pp. 161–183. Springer, Heidelberg (2000)
van der Aalst, W.: Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer (2011)
van der Aalst, W.M., Schonenberg, M., Song, M.: Time prediction based on process mining. Information Systems 36(2), 450–475 (2011)
Hall, R.W.: Queueing Methods: For Services and Manufacturing. Prentice-Hall, Englewood Cliffs (1991)
Bolch, G., Greiner, S., de Meer, H., Trivedi, K.S.: Queueing networks and Markov chains - modeling and performance evaluation with computer science applications. Wiley (2006)
Object Management Group (OMG): Business Process Model and Notation, BPMN (2011)
Kendall, D.G.: Stochastic processes occurring in the theory of queues and their analysis by the method of the imbedded markov chain. The Annals of Mathematical Statistics 24(3), 338–354 (1953)
Nakibly, E.: Predicting waiting times in telephone service systems. Master’s thesis, Technion–Israel Institute of Technology (2002)
Houston, M.B., Bettencourt, L.A., Wenger, S.: The relationship between waiting in a service queue and evaluations of service quality: A field theory perspective. Psychology and Marketing 15(8), 735–753 (1998)
Carmon, Z., Kahneman, D.: The experienced utility of queuing: real time affect and retrospective evaluations of simulated queues. Technical report, Duke University (1996)
Larson, R.C.: Perspectives on queues: Social justice and the psychology of queueing. Operations Research 35(6), 895–905 (1987)
Manning, C.D., Raghavan, P., Schütze, H.: Introduction to Information Retrieval. Cambridge University Press (2008)
Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning. Springer Series in Statistics. Springer New York Inc., New York (2001)
Ibrahim, R., Whitt, W.: Real-time delay estimation based on delay history. Manufacturing and Service Operations Management 11(3), 397–415 (2009)
Schruben, L., Kulkarni, R.: Some consequences of estimating parameters for the m/m/1 queue. Operations Research Letters 1(2), 75–78 (1982)
Brown, L., Gans, N., Mandelbaum, A., Sakov, A., Shen, H., Zeltyn, S., Zhao, L.: Statistical analysis of a telephone call center. Journal of the American Statistical Association 100(469), 36–50 (2005)
Whitt, W.: Stochastic-process limits: an introduction to stochastic-process limits and their application to queues. Springer (2002)
Nguyen, V.: The trouble with diversity: Fork-join networks with heterogeneous customer population. The Annals of Applied Probability, 1–25 (1994)
Gans, N., Koole, G., Mandelbaum, A.: Telephone call centers: Tutorial, review, and research prospects. Manufacturing & Service Operations Management 5(2), 79–141 (2003)
van der Aalst, W., Nakatumba, J., Rozinat, A., Russell, N.: Business process simulation: How to get it right. BPM Center Report BPM-08-07 (2008), BPMcenter.org
Rogge-Solti, A., Weske, M.: Prediction of remaining service execution time using stochastic petri nets with arbitrary firing delays. In: Basu, S., Pautasso, C., Zhang, L., Fu, X. (eds.) ICSOC 2013. LNCS, vol. 8274, pp. 389–403. Springer, Heidelberg (2013)
Woodside, C.M., Stanford, D.A., Pagurek, B.: Optimal prediction of queue lengths and delays in gi/m/m multiserver queues. Operations Research 32(4), 809–817 (1984)
Whitt, W.: Predicting queueing delays. Management Science 45(6), 870–888 (1999)
Folino, F., Guarascio, M., Pontieri, L.: Discovering Context-Aware Models for Predicting Business Process Performances. In: Meersman, R., et al. (eds.) OTM 2012, Part I. LNCS, vol. 7565, pp. 287–304. Springer, Heidelberg (2012)
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Senderovich, A., Weidlich, M., Gal, A., Mandelbaum, A. (2014). Queue Mining – Predicting Delays in Service Processes. In: Jarke, M., et al. Advanced Information Systems Engineering. CAiSE 2014. Lecture Notes in Computer Science, vol 8484. Springer, Cham. https://doi.org/10.1007/978-3-319-07881-6_4
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DOI: https://doi.org/10.1007/978-3-319-07881-6_4
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