DocumentCode :
3695828
Title :
Discovering process model from incomplete log using process mining
Author :
Ivona Zakarija;Frano Škopljanac-Mačina;Bruno Blašković
Author_Institution :
University of Dubrovnik, Cira Ć
fYear :
2015
Firstpage :
117
Lastpage :
120
Abstract :
This paper gives an overview of relevant research in the area of process mining. Process mining techniques are able to extract knowledge from event logs. The major objective of process mining is to discover, monitor and improve real processes. Process mining aims to exploit event data in a meaningful way to identify and anticipate problems, and recommend countermeasures. Additionally, process mining places the existing massive volumes of data in the context of processes. Since extracting data is an integral part of any process mining procedure, data preparation or data pre-processing requires certain efforts. Examples have been given to indicate how the chosen process mining technique deals with incompleteness in the event log data. Experiments have been made on the real data collected from information system for accommodation services.
Keywords :
"Data mining","Monitoring","Big data","Classification algorithms","Companies"
Publisher :
ieee
Conference_Titel :
ELMAR (ELMAR), 2015 57th International Symposium
Print_ISBN :
978-953-184-209-9
Type :
conf
DOI :
10.1109/ELMAR.2015.7334510
Filename :
7334510
Link To Document :
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