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An empirical evaluation of unsupervised event log abstraction techniques in process mining.

, , , and . Inf. Syst., (March 2024)

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AITIA-PM: Discovering the true causes of events in a process mining context., , and . Eng. Appl. Artif. Intell., 126 (Part D): 107145 (November 2023)Extensions to the bupaR Ecosystem: An Overview., , , , , , , and . ICPM Doctoral Consortium / Tools, volume 2703 of CEUR Workshop Proceedings, page 43-46. CEUR-WS.org, (2020)An empirical evaluation of unsupervised event log abstraction techniques in process mining., , , and . Inf. Syst., (March 2024)Fuzzy Cognitive Maps: A Business Intelligence Discussion., , , , , and . KES-IDT (1), volume 142 of Smart Innovation, Systems and Technologies, page 89-98. Springer, (2019)DaQAPO: Supporting flexible and fine-grained event log quality assessment., , and . Expert Syst. Appl., (2022)Root Cause Analysis in Process Mining with Probabilistic Temporal Logic., , and . ICPM Workshops, volume 433 of Lecture Notes in Business Information Processing, page 73-84. Springer, (2021)Mining Behavioural Patterns from Event Data to Enable Context-Aware Root Cause Analysis (Extended Abstract).. ICPM Doctoral Consortium / Tools, volume 2703 of CEUR Workshop Proceedings, page 9-10. CEUR-WS.org, (2020)Unsupervised Event Abstraction in a Process Mining Context: A Benchmark Study., , and . ICPM Workshops, volume 406 of Lecture Notes in Business Information Processing, page 82-93. Springer, (2020)