Preserving complex object-centric graph structures to improve machine learning tasks in process mining
Engineering Applications of Artificial Intelligence, vol. 125, pp. 106764
Authors 3
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Affiliation as printed
Chair of Process and Data Science, RWTH Aachen University, Ahornstraße 55, Aachen, 52074, North Rhine-Westphalia, Germany
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Affiliation as printed
Chair of Process and Data Science, RWTH Aachen University, Ahornstraße 55, Aachen, 52074, North Rhine-Westphalia, Germany
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RWTH Aachen University · Fraunhofer Institute for Applied Information Technology
Affiliation as printed
Celonis SE, Theresienstr. 6, Munich, 80333, Bavaria, Germany
Chair of Process and Data Science, RWTH Aachen University, Ahornstraße 55, Aachen, 52074, North Rhine-Westphalia, Germany
Fraunhofer FIT, Schloß Birlinghoven, Konrad-Adenauer-Straße, Sankt Augustin, 53757, North Rhine-Westphalia, Germany
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References 89
-
W2963107557details pending0citations
-
W6726873649details pending0citations
-
W3169710019details pending0citations
-
W6681029592details pending0citations
-
W6732910048details pending0citations
-
W6799874364details pending0citations
-
W6803313354details pending0citations
-
W6810342540details pending0citations
-
W6840098353details pending0citations
-
W6841133072details pending0citations
-
W6843184940details pending0citations
-
W6604003107details pending0citations
-
W6637559767details pending0citations
-
W6643836269details pending0citations