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Towards Traditional Simulation Models of Context Using Process Mining

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Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoComputational Intelligence, Communication Systems and Networks (CICSyN), 2015 7th International Conference on
KustantajaIEEE
Sivut70-75
Sivumäärä6
ISBN (painettu)9781467370165
DOI - pysyväislinkit
TilaJulkaistu - 2015
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaINTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE, COMMUNICATION SYSTEMS AND NETWORKS (CICSYN) -
Kesto: 1 tammikuuta 1900 → …

Conference

ConferenceINTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE, COMMUNICATION SYSTEMS AND NETWORKS (CICSYN)
LyhennettäCICSyN
Ajanjakso1/01/00 → …

Tiivistelmä

Context (sensor) systems are hard to model: they require constant updating and insightful approaches, especially considering the increasing data volume, variety, and generation rate of contemporary networking paradigms, like the Internet of Things. In this paper, we argue that intelligent process models can be mined to look at the actual system activity from alternative context perspectives, i.e., perspectives observable from the sensor attributes themselves. We explain how the close relationship between the models derived using Process Mining, and Event-Driven Simulation can be exploited to help not only better understand what is happening in such systems but also provide alternative models for the intelligent solutions they support, such as context inference. We demonstrate this using a real-world example and discuss the feasibility of extending these alternative process models to be viewed as simulation. We envision automated steps that would result in traditional simulation models of context using Process Mining.

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