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Discovery of Frequent Episodes in Event Logs · Study

WorkDiscovery of Frequent Episodes in Event Logs

Maikel Leemans2015

OA

Workbronze2015

Discovery of Frequent Episodes in Event Logs

Maikel Leemans · Wil M. P. van der Aalst

65 citations·0/0 files stored·Lecture notes in business information processing

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Business Process Modeling and Analysis Data Mining Algorithms and Applications Time Series Analysis and Forecasting

Abstract

No abstract was published for this record.

Citations in this library

Stored only when both papers are in the corpus — 65 citations exist upstream.

References

2004Workflow mining: discovering process models from event logs 2011Process Mining 2011Process Mining: Discovery, Conformance and Enhancement of Business Processes 2007Fuzzy Mining – Adaptive Process Simplification Based on Multi-perspective Metrics 2007Genetic process mining: an experimental evaluation 2006Process mining with the HeuristicsMiner algorithm 2008Process mining: a two-step approach to balance between underfitting and overfitting 2008Towards comprehensive support for organizational mining

Cited by

2018Guided Process Discovery – A pattern-based approach 2015Process mining in software systems: Discovering real-life business transactions and process models from distributed systems 2017Extracting useful knowledge from event logs: A frequent itemset mining approach 2022Partial-order-based process mining: a survey and outlook 2018Mining frequent patterns in process models 2020Event-log abstraction using batch session identification and clustering 2018Discovering anomalous frequent patterns from partially ordered event logs 2019A Profile Clustering Based Event Logs Repairing Approach for Process Mining

Details

Year2015

Typeother

Published2015-01-01

VenueLecture notes in business information processing

ISSN-L1865-1348

Languageen

Citations65

Files0 public / 0

ShelfBusiness Process Modeling and Analysis

Identifiers

doi10.1007/978-3-319-27243-6_1

openalex_workW794897257

Links

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