A self-portrayal of GI Junior Fellow Matthias Weidlich: Event-driven analysis of service processes
| dc.contributor.author | Weidlich, Matthias | |
| dc.date.accessioned | 2021-06-21T10:07:06Z | |
| dc.date.available | 2021-06-21T10:07:06Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | In domains such as e-commerce, logistics, or healthcare, the conduct of service processes is widely supported by information systems and event data is generated continuously during process execution. Such event data constitutes a valuable source of information to monitor and improve the respective service processes. My research focuses on models and methods to support event-driven analysis of service processes. Specifically, I study how event logs produced by information systems are used to automatically construct models for qualitative and quantitative analysis. Aiming at online assessment and predictive analysis of a process' behaviour, I develop monitoring techniques that utilise streams of event data produced by diverse sources. Architectures that enable efficient handling of event streams are another focal point of my research. In this article, I outline some of the related research questions and highlight my recent results in these areas. | en |
| dc.identifier.doi | 10.1515/itit-2017-0035 | |
| dc.identifier.pissn | 2196-7032 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/36591 | |
| dc.language.iso | en | |
| dc.publisher | De Gruyter | |
| dc.relation.ispartof | it - Information Technology: Vol. 60, No. 1 | |
| dc.subject | Information systems | |
| dc.subject | process analysis | |
| dc.subject | process mining | |
| dc.subject | stream processing | |
| dc.title | A self-portrayal of GI Junior Fellow Matthias Weidlich: Event-driven analysis of service processes | en |
| dc.type | Text/Journal Article | |
| gi.citation.endPage | 54 | |
| gi.citation.publisherPlace | Berlin | |
| gi.citation.startPage | 51 |