Seeliger, Alexander ; Lüttgen, Stefan ; Mühlhäuser, Max ; Nolle, Timo (2020)
Extended synthetic event logs for multi-perspective trace clustering.
Forschungsdaten, Bibliographie
Kurzbeschreibung (Abstract)
The data set contains an extended set of event logs for evaluating multi-perspective trace clustering approaches in process mining. Event logs were randomly generated from 5 different process models of different complexity levels. The attribute "cluster" refers to the ground truth label. Clusters can only be correctly identified when considering both, the data and the control flow perspective (attributes and trace). The extended dataset contains more noise levels as well as a different generation process regarding the case attributes.
| Typ des Eintrags: | Forschungsdaten |
|---|---|
| Erschienen: | 2020 |
| Autor(en): | Seeliger, Alexander ; Lüttgen, Stefan ; Mühlhäuser, Max ; Nolle, Timo |
| Art des Eintrags: | Bibliographie |
| Titel: | Extended synthetic event logs for multi-perspective trace clustering |
| Sprache: | Englisch |
| Publikationsjahr: | 30 Mai 2020 |
| Ort: | Darmstadt |
| URL / URN: | https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2415 |
| Kurzbeschreibung (Abstract): | The data set contains an extended set of event logs for evaluating multi-perspective trace clustering approaches in process mining. Event logs were randomly generated from 5 different process models of different complexity levels. The attribute "cluster" refers to the ground truth label. Clusters can only be correctly identified when considering both, the data and the control flow perspective (attributes and trace). The extended dataset contains more noise levels as well as a different generation process regarding the case attributes. |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Telekooperation |
| Hinterlegungsdatum: | 21 Feb 2022 10:01 |
| Letzte Änderung: | 22 Feb 2022 15:16 |
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