Paper Info
Title
Knowledge Acquisition from EPC Models for Extraction of Process Patterns in Engineering Domains
Abstract
This paper presents an approach for the automated extraction of process patterns from Event-driven Process Chain (EPC) models in engineering domains. The manually extraction of process patterns (semantically described reference building blocks) is a labor-intensive, tedious and cumbersome task. The introduced approach comprises the three stages knowledge acquisition, process pattern extraction and generic pattern construction that are conducted automated. The presented approach is characterized by exploiting the implicit semantics of natural language terms associated with EPC model elements. Semantic patterns are employed to analyze the lexical structure of these terms and to relate them to instances of a reference ontology. Thus semantically annotated EPC model elements are input for subsequent process pattern extraction. The semantic annotation allows during pattern extraction to identify process goals of EPC functions and to organize goals into hierarchies. During generic process pattern construction, common goals of different process patterns give rise to construct generic process patterns.
Year
Venue
Keywords
2008
Multikonferenz Wirtschaftsinformatik
event driven process chain,natural language
Field
DocType
Citations 
Ontology,Semantic annotation,Computer science,Knowledge management,Natural language,Natural language processing,Artificial intelligence,Hierarchy,Process patterns,Semantics,Knowledge acquisition
Conference
9
PageRank 
References 
Authors
0.58
11
3
Name
Order
Citations
PageRank
Andreas Bögl1192.49
Maximilian Kobler2101.00
Michael Schrefl31375523.09