In recent years, investigating opportunities to support knowledgeintensive business processes has gained increasing momentum in the research community. Novel contributions that introduce paradigms addressing the need for process execution flexibility form an alternative to traditional workflow management approaches and are mostly subsumed under the concept of adaptive case management (ACM). However, many of these approaches omit mining any kind of knowledge about such processes. This is because there is a gap between process mining, which works well for structured processes, and ACM, which mainly focuses on information system support for task management and collaboration using heterogeneous data sources. In this paper, we strive to bridge this gap by introducing a method for mining knowledge-intensive processes. It is part of agendadriven case management, an ACM approach that follows the idea of mining common execution patterns while a case manager handles a flexible agenda.
|Titill gistiútgáfu||Proceedings of the 15th International Conference on Knowledge Technologies and Data-Driven Business, i-KNOW 2015|
|Ritstjórar||Harald Sack, Stefanie Lindstaedt, Tobias Ley|
|Útgefandi||Association for Computing Machinery (ACM)|
|Útgáfustaða||Útgefið - 21 okt. 2015|
|Viðburður||15th International Conference on Knowledge Technologies and Data-Driven Business, i-KNOW 2015 - Graz, Austurríki|
Tímalengd: 21 okt. 2015 → 22 okt. 2015
|Nafn||ACM International Conference Proceeding Series|
|Ráðstefna||15th International Conference on Knowledge Technologies and Data-Driven Business, i-KNOW 2015|
|Tímabil||21/10/15 → 22/10/15|
© 2015 ACM.