Abstract
Process Mining (PM) encompasses a number of methodologies designed for extracting knowledge from event logs, typically recorded by operational information systems like ERPs, Workflow Management Systems or other process-aware enterprise systems. The structured nature of processes implemented in these systems has led to the development of effective techniques for conformance checking (check if a real execution trace conforms to a predefined process schema) or process discovery (synthesize a process schema from a set of real execution traces recorded in the trace log) [1]. However in many knowledge-intensive domains, like e.g. health care, emergency management, research and innovation development, processes are typically characterized by little or no structure, since the flow of activities strongly depends on context-dependent decisions that should rely on human knowledge. Consequently, classical process discovery techniques usually provide limited support in analyzing these processes. As a further issue, in these domains an integrated information system may not even exist, requiring to integrate a number of independent event logs.
Original language | English |
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Title of host publication | 2015 International Conference on High Performance Computing & Simulation (HPCS) |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 323-324 |
ISBN (Electronic) | 978-1-4673-7813-0 |
ISBN (Print) | 978-1-4673-7812-3 |
DOIs | |
Publication status | Published - 2015 |
Externally published | Yes |
Event | 2015 International Conference on High Performance Computing & Simulation (HPCS 2015) - Hilton Amsterdam Hotel, Amsterdam, Netherlands Duration: 20 Jul 2015 → 24 Jul 2015 http://hpcs2015.cisedu.info/ |
Conference
Conference | 2015 International Conference on High Performance Computing & Simulation (HPCS 2015) |
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Abbreviated title | HPCS 2015 |
Country/Territory | Netherlands |
City | Amsterdam |
Period | 20/07/15 → 24/07/15 |
Other | "The 13th Annual Meeting" |
Internet address |