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2015
Springer

Event Log Visualisation with Conditional Partial Order Graphs: from Control Flow to Data

3 years 7 months ago
Event Log Visualisation with Conditional Partial Order Graphs: from Control Flow to Data
Process mining techniques rely on event logs: the extraction of a process model (discovery) takes an event log as the input, the adequacy of a process model (conformance) is checked against an event log, and the enhancement of a process model is performed by using available data in the log. Several notations and formalisms for event log representation have been proposed in the recent years to enable efficient algorithms for the aforementioned process mining problems. In this paper we show how Conditional Partial Order Graphs (CPOGs), a recently introduced formalism for compact representation of families of partial orders, can be used in the process mining field, in particular for addressing the problem of compact and easy-to-comprehend visualisation of event logs with data. We present algorithms for extracting both the control flow as well as the relevant data parameters from a given event log and show how CPOGs can be used for efficient and effective visualisation of the obtained r...
Andrey Mokhov, Josep Carmona
Added 16 Apr 2016
Updated 16 Apr 2016
Type Journal
Year 2015
Where APN
Authors Andrey Mokhov, Josep Carmona
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