The ROAD from Sensor Data to Process Instances via Interaction Mining View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2016

AUTHORS

Arik Senderovich , Andreas Rogge-Solti , Avigdor Gal , Jan Mendling , Avishai Mandelbaum

ABSTRACT

Process mining is a rapidly developing field that aims at automated modeling of business processes based on data coming from event logs. In recent years, advances in tracking technologies, e.g., Real-Time Locating Systems (RTLS), put forward the ability to log business process events as location sensor data. To apply process mining techniques to such sensor data, one needs to overcome an abstraction gap, because location data recordings do not relate to the process directly. In this work, we solve the problem of mapping sensor data to event logs based on process knowledge. Specifically, we propose interactions as an intermediate knowledge layer between the sensor data and the event log. We solve the mapping problem via optimal matching between interactions and process instances. An empirical evaluation of our approach shows its feasibility and provides insights into the relation between ambiguities and deviations from process knowledge, and accuracy of the resulting event log. More... »

PAGES

257-273

Book

TITLE

Advanced Information Systems Engineering

ISBN

978-3-319-39695-8
978-3-319-39696-5

From Grant

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-39696-5_16

DOI

http://dx.doi.org/10.1007/978-3-319-39696-5_16

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1040148411


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