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Song, Minseok
Business Process Intelligence(BPI) Lab
Research Interests
  • Process mining
  • Social network analysis/Organizational structure analysis
  • Process knowledge management
  • Business process analysis, simulation, and optimization
  • Data mining/business intelligence

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An outlook on semantic business process mining and monitoring

Cited 18 times inthomson ciCited 8 times inthomson ci
Title
An outlook on semantic business process mining and monitoring
Author
Alves De Medeiros, A.K.Pedrinaci, C.Van Der Aalst, W.M.P.Domingue, J.Song, MinseokRozinat, A.Norton, B.Cabral, L.
Keywords
WEB SERVICES;  SYSTEMS;  MANAGEMENT
Issue Date
2007
Publisher
Springer Verlag
Citation
LECTURE NOTES IN COMPUTER SCIENCE, v.4806, no.part2, pp.1244 - 1255
Abstract
Semantic Business Process Management (SBPM) has been proposed as an extension of BPM with Semantic Web and Semantic Web Services (SWS) technologies in order to increase and enhance the level of automation that can be achieved within the BPM life-cycle. In a nutshell, SBPM is based on the extensive and exhaustive conceptualization of the BPM domain so as to support reasoning during business processes modelling, composition, execution, and analysis, leading to important enhancements throughout the life-cycle of business processes. An important step of the BPM life-cycle is the analysis of the processes deployed in companies. This analysis provides feedback about how these processes are actually being executed (like common control-flow paths, performance measures, detection of bottlenecks, alert to approaching deadlines, auditing, etc). The use of semantic information can lead to dramatic enhancements in the state-of-the-art in analysis techniques. In this paper we present an outlook on the opportunities and challenges on semantic business process mining and monitoring, thus paving the way for the implementation of the next generation of BPM analysis tools.
URI
https://scholarworks.unist.ac.kr/handle/201301/9021
ISSN
0302-9743
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