Title :
Using a Flow Graph to Represent Data Flow and Dependency in Event Logs
Author :
Abdulelah Aldahami;Yuefeng Li;Taizan Chan
Author_Institution :
Inf. Technol. Dept., Saudi Arabia Monetary Agency (SAMA), Riyadh, Saudi Arabia
Abstract :
The idea of extracting knowledge in process mining is a descendant of data mining. Both mining disciplines emphasise data flow and relations among elements in the data. Unfortunately, challenges have been encountered when working with the data flow and relations. One of the challenges is that the representation of the data flow between a pair of elements or tasks is insufficiently simplified and formulated, as it considers only a one-to-one data flow relation. In this paper, we discuss how the effectiveness of knowledge representation can be extended in both disciplines. To this end, we introduce a new representation of the data flow and dependency formulation using a flow graph. The flow graph solves the issue of the insufficiency of presenting other relation types, such as many-to-one and one-to-many relations. As an experiment, a new evaluation framework is applied to the Teleclaim process in order to show how this method can provide us with more precise results when compared with other representations.
Keywords :
"Data mining","Heuristic algorithms","Data models","Current measurement","Petri nets","Mathematical model","Process control"
Conference_Titel :
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2015 IEEE / WIC / ACM International Conference on
DOI :
10.1109/WI-IAT.2015.213