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Decision Point Analysis of Time Series Data in Process-Aware Information Systems

Abstract

The majority of process mining techniques focuses on con- trol flow. Decision Point Analysis (DPA) exploits additional data attachments within log files to determine attributes decisive for branching of process paths within discovered process models. DPA considers only single attribute values. However, in many applications, the process environment provides additional data in form of consecutive measurement values such as blood pressure or container temperature. We introduce the DPATimeSeries method as an iterative process for exploiting time se- ries data by combining process mining and data mining techniques. The method also offers different approaches for incorporating time series data into log files in order to enable existing process mining techniques to be applied. Finally, we provide the simulation environment DPATimeSeriesSim to produce log files and time series data. The DPATimeSeries method is evaluated based on an application scenario from the logistics domain.

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Citation
Category
Paper in Conference Proceedings or in Workshop Proceedings (Short Paper in Proceedings)
Event Title
CAISE Forum 2014
Divisions
Data Analytics and Computing
Knowledge Engineering
Workflow Systems and Technology
Event Location
Thessaloniki
Event Type
Conference
Event Dates
June 2014
Series Name
ceur-ws.org/Vol-1164/
Page Range
pp. 33-40
Date
June 2014
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