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dc.contributor.authorSeeliger, Alexander
dc.contributor.authorNolle, Timo
dc.contributor.authorMühlhäuser, Max
dc.date.accessioned2020-05-25T09:12:27Z
dc.date.available2020-05-25T09:12:27Z
dc.date.issued2018-09-09
dc.identifier.urihttps://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2338
dc.descriptionThe data set contains a 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).en_US
dc.relationIsSupplementTo;DOI;10.1007/978-3-319-98648-7_17
dc.rightsCreative Commons Attribution 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectEvent logen_US
dc.subjectProcess miningen_US
dc.subjectSyntheticen_US
dc.subjectTrace clusteringen_US
dc.subject.classification409-06 Informationssysteme, Prozess- und Wissensmanagementen_US
dc.subject.ddc004
dc.titleSynthetic event logs for multi-perspective trace clusteringen_US
dc.typeDataseten_US
tud.projectHMWK/LOEWE | 522/17-04 | DRUP: Deep Reasoningen_US
tud.projectBund/BMBF | 01IS17050 | Software Campus 2.0en_US


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Creative Commons Attribution 4.0
Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0