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Process Mining Workshops

ICPM 2024 International Workshops, Lyngby, Denmark, October 14–18, 2024, Revised Selected Papers

dc.contributor.editorDelgado, Andrea
dc.contributor.editorSlaats, Tijs
dc.date.accessioned2025-11-24T10:03:44Z
dc.date.available2025-11-24T10:03:44Z
dc.date.issued2025
dc.date.submitted2025-04-14T12:57:03Z
dc.identifierONIX_20250414_9783031822254_20
dc.identifierhttps://library.oapen.org/handle/20.500.12657/100762
dc.identifier.urihttps://doab-dev.siscern.org/handle/20.500.12854/204777
dc.description.abstractThis book constitutes the revised accepted papers of several workshops which were held in conjunction with the 6th International Conference on Process Mining, ICPM 2024, held in Lyngby, Denmark, during October 2024. The 56 revised full papers presented in this book were carefully reviewed and selected from 126 submissions. The papers presented in this volume stem from the following workshops: – 9th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI) – 3rd International Workshop on Education Meets Process Mining (EduPM) – 3rd International Workshop on Collaboration Mining for Distributed Systems (CoMinDS) – 5th International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) – 5th International Workshop on Event Data and Behavioral Analytics (EdbA) – 7th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) – 1st International Workshop on Empirical Research in Process Mining (ERPM) – 1st International Workshop on Generative Artificial Intelligence for Process Mining (GenAI4PM) – 4th International Workshop on Stream Management & Analytics for Process Mining (SMA4PM) – 1st International Workshop on Process Mining for Sustainability (PM4S).
dc.languageEnglish
dc.relation.ispartofseriesLecture Notes in Business Information Processing
dc.rightsopen access
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data mining
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQE Expert systems / knowledge-based systems
dc.subject.classificationthema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJQ Business mathematics and systems
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UX Applied computing::UXJ Computer applications in the social and behavioural sciences
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UX Applied computing::UXT Computer applications in industry and technology
dc.subject.otherBusiness Process Management
dc.subject.otherBusiness Intelligence
dc.subject.otherDecision Supprt Systems
dc.subject.otherArtificial Intelligence
dc.subject.otherMachine Learnig
dc.subject.otherHealthcare Systems
dc.subject.otherConformance Checking
dc.subject.otherInformation Systems
dc.subject.othercomputers and education
dc.subject.otherempirical research
dc.subject.otherenterprise modeling
dc.titleProcess Mining Workshops
dc.title.alternativeICPM 2024 International Workshops, Lyngby, Denmark, October 14–18, 2024, Revised Selected Papers
dc.typebook
oapen.identifier.doi10.1007/978-3-031-82225-4
oapen.relation.isPublishedBy9fa3421d-f917-4153-b9ab-fc337c396b5a
oapen.relation.isFundedBybd43f9c4-5f09-408d-b27e-9dfa94138dab
oapen.relation.isbn9783031822247
oapen.imprintSpringer Nature Switzerland
oapen.pages781
oapen.place.publicationCham
oapen.grant.number[...]
dc.relationisFundedBybd43f9c4-5f09-408d-b27e-9dfa94138dab
dc.seriesnumber533


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