Abstract
Having access to the right information on business processes is crucial to the proper and efficient execution of all sorts of activities, such as the assessment of mortgage applications, manufacturing of goods, as well as the treatment of patients. A major challenge here is that information related to a single process is often spread out over various models, documents, and systems. This fragmentation can have disastrous consequences for an organizations operations. It can, for example, lead to delays, wastes of money, and even violations of rules and laws. The work presented in this thesis tackles these problems with algorithms that can automatically compare process information stemming from various sources. These techniques, among others, enable the detection of contradictions between the sources and improve the ability of organizations to monitor their compliance to rules and regulations.
| Original language | English |
|---|---|
| Title of host publication | BPMTracks 2018 - BPM 2018 Dissertation Award, Demonstration, and Industrial Track |
| Subtitle of host publication | Proceedings of the Dissertation Award, Demonstration, and Industrial Track at BPM 2018, co-located with 16th International Conference on Business Process Management (BPM 2018) |
| Chapter | 4 |
| Pages | 16-20 |
| Number of pages | 5 |
| Publication status | Published - 2018 |
| Event | 2018 Dissertation Award, Demonstration, and Industrial Track at BPM, BPMTracks 2018 - Sydney, Australia Duration: 9 Sept 2018 → … |
Publication series
| Name | CEUR Workshop Proceedings |
|---|---|
| Publisher | CEUR Workshop Proceedings |
| Volume | 2196 |
| ISSN (Print) | 1613-0073 |
Conference
| Conference | 2018 Dissertation Award, Demonstration, and Industrial Track at BPM, BPMTracks 2018 |
|---|---|
| Country/Territory | Australia |
| City | Sydney |
| Period | 9/09/18 → … |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 16 Peace, Justice and Strong Institutions
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