2014 | OriginalPaper | Buchkapitel
Queue Mining – Predicting Delays in Service Processes
verfasst von : Arik Senderovich, Matthias Weidlich, Avigdor Gal, Avishai Mandelbaum
Erschienen in: Advanced Information Systems Engineering
Verlag: Springer International Publishing
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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.