Process Mining Workshops -

Process Mining Workshops

ICPM 2020 International Workshops, Padua, Italy, October 5–8, 2020, Revised Selected Papers
Buch | Softcover
XIV, 400 Seiten
2021 | 1st ed. 2021
Springer International Publishing (Verlag)
978-3-030-72692-8 (ISBN)
80,24 inkl. MwSt
This book constitutes revised selected papers from the International Workshops held at the Second International Conference on Process Mining, ICPM 2020, which took place during October 4-9, 2020. The conference was planned to take place in Padua, Italy, but had to be held online due to the COVID-19 pandemic.

The conference focuses on the area of process mining research and practice, including theory, algorithmic challenges, and applications. The co-located workshops provided a forum for novel research ideas. The 29 papers included in this volume were carefully reviewed and selected from 59 submissions. They stem from the following workshops:

1st International Workshop on Event Data and Behavioral Analytics (EDBA)

1st International Workshop on Leveraging Machine Learning in Process Mining (ML4PM)

1st International Workshop on Streaming Analytics for Process Mining (SA4PM'20)

5th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI)

3rd International Workshop on Process-Oriented Data Science for Healthcare (PODS4H)

1st International Workshop on Trust and Privacy in Process Analytics (TPPA)

 

1st International Workshop on Event Data and Behavioral Analytics (EDBA).- Visually Representing History Dependencies in Event Logs.- Analysis of Business Process Batching using Causal Event Models.- Process Procespecting to Improve Renewable Energy Interconnection Queues: A Case Study.- Automated Discovery of Process Models with True Concurrency and Inclusive Choices.- A Novel Approach to Discover Switch Behaviours in Process Mining.- Process Model Discovery from Sensor Event Data.- Unsupervised Event Abstraction in a Process Mining Context: A Benchmark Study.- 1st International Workshop on Leveraging Machine Learning in Process Mining (ML4PM).- Predicting Remaining Cycle Time from Ongoing Cases: A Survival Analysis-based Approach.- Time Matters:Time-Aware LSTMs for Predictive Business Process Monitoring.- A preliminary study on the application of Reinforcement Learning for Predictive Process Monitoring.- An Alignment Cost-Based Classi cation of Log Traces Using Machine-Learning.- Improving the Extraction of Process Annotations from Text with Inter-Sentence Analysis.- Case2vec: Advances in Representation Learning for Business Processes.- Supervised Conformance Checking using Recurrent Neural Network Classifiers.- 1st International Workshop on Streaming Analytics for Process Mining (SA4PM'20).- Online Anomaly Detection Using Statistical Leverage for Streaming Business Process Events.- Concept Drift Detection on Streaming Data with Dynamic Outlier Aggregation.- OTOSO: Online Trace Ordering for Structural Overviews.- Performance Skyline: Inferring Process Performance Models from Interval Events.- 5th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI 2020).- Alignment Approximation for Process Trees.- Stochastic Process Discovery By Weight Estimation.- Graph-based Process Mining.- Third International Workshop on Process-Oriented Data Science for Healthcare (PODS4H).- A Process Mining approach to statistical analysis: application to a real-world advanced melanoma dataset.- Process Mining of Disease Trajectories in MIMIC-III: A Case Study.- The Need for Interactive Data-Driven Process Simulation in Healthcare: A Case Study.- Process mining on the extended event log to analyse the system usage during healthcare processes (Case study: the GP Tab usage during chemotherapy treatments).- Process Mining on FHIR - An Open Standards-Based Process Analytics Suite for Healthcare.- Deriving a sophisticated clinical pathway based on patient conditions from electronic health record data.- Exploration on How Global Warming Affects Emergency Services.- 1st Workshop on Trust and Privacy in Process Analytics (TPPA).- Towards Quantifying Privacy in Process Mining.

Erscheinungsdatum
Reihe/Serie Lecture Notes in Business Information Processing
Zusatzinfo XIV, 400 p. 152 illus., 101 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 635 g
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Schlagworte Applications • business process management • Computer Science • conference proceedings • conformance checking • Data Science • Decision Support Systems • Event data • Informatics • information systems • machine learning • Petri Nets • Predictive Process Monitoring • process analytics • process discovery • Process Mining • Process Querying • Research • Streaming analytics
ISBN-10 3-030-72692-4 / 3030726924
ISBN-13 978-3-030-72692-8 / 9783030726928
Zustand Neuware
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