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An Ontology Framework to Enhance Business Process Mining and Analysis

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dc.contributor.advisor Dr. Paul Janecek
dc.contributor.author Jareevongpiboon, Wirat
dc.contributor.other Dr. Vatcharaporn Esichaikul (Member) Dr. Poompat Saengudomlert (Member)
dc.date.accessioned 2015-01-20T06:46:46Z
dc.date.available 2015-01-20T06:46:46Z
dc.date.issued 2013-12
dc.identifier.other AIT Diss no.CS-13-05 en_US
dc.identifier.uri http://www.cs.ait.ac.th/xmlui/handle/123456789/667
dc.description.abstract The largest obstacle for automating Business Process Management (BPM) is the lack of machine processable semantics between the business and IT levels. To overcome this problem, Semantic Business Process Management (SBPM) proposes the integration of BPM, Semantic Web and Semantic Web Services (SWS) technologies. Ontology plays a key role in providing knowledge to these technologies to enhance the level of automation in all phases of BPM. This thesis proposes a solution to SBPM focusing on business process mining and analysis, a post-execution phase of BPM. We introduce an ontological framework and methodology that combines domain and company specific ontologies and databases to obtain multiple layers of semantics for business processes. We also present an approach to incorporate these semantics from the proposed ontology framework to enhance the levels of abstraction in mining and analysis. We evaluated this framework and approach with a real case study from the apparel domain using a prototype that extends the tools developed by the SUPER project and techniques developed in the Process Mining Framework (ProM). The findings show that semantically enriching process execution data with this approach can successfully raise analysis from the syntactic to the semantic level, and enable multiple perspectives of analysis on business processes. Combining this approach with complementary research in SBPM can provide results comparable to multidimensional analysis in data warehouse and OLAP technologies. The approach and prototype described in this thesis improve the richness of semantics available for open-source process mining and analysis tools like ProM, as well as the richness and detail of the resulting analysis. en_US
dc.description.sponsorship Office of the Higher Education Commission, Thailand en_US
dc.publisher AIT en_US
dc.title An Ontology Framework to Enhance Business Process Mining and Analysis en_US
dc.type Dissertation en_US


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