DocumentCode :
2368997
Title :
Process mining for semantic business process modeling
Author :
Lautenbacher, Florian ; Bauer, Bernhard ; Förg, Sebastian
Author_Institution :
Programming Distrib. Syst. Lab., Univ. of Augsburg, Augsburg, Germany
fYear :
2009
fDate :
1-4 Sept. 2009
Firstpage :
45
Lastpage :
53
Abstract :
Business processes are captured by models that serve as a basis for communication and training purposes, but this modeling is still a time consuming manual job. Semantic annotation of process models in combination with AI planning approaches can contribute to solve this drawback enabling an automatic creation of process models. But the semantic annotated process fragments necessary for starting the planning are often missing at all or not up-to-date anymore. Therefore, this work describes an approach for the semantic annotation and semantic-based planning of process models and introduces Cystid, an integration of Process Mining algorithms and semantic-based planning.
Keywords :
business process re-engineering; data mining; planning (artificial intelligence); process planning; programming language semantics; specification languages; AI planning; Cystid algorithm; process mining; semantic business process modeling; semantic process annotation; semantic-based process planning; Artificial intelligence; Business communication; Companies; Engines; Enterprise resource planning; Information systems; Libraries; Management training; Ontologies; Process planning; Process Mining; Process Models; SBPM;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Enterprise Distributed Object Computing Conference Workshops, 2009. EDOCW 2009. 13th
Conference_Location :
Auckland
Print_ISBN :
978-1-4244-5563-8
Type :
conf
DOI :
10.1109/EDOCW.2009.5332017
Filename :
5332017
Link To Document :
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