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Data-Driven Process Discovery and Analysis 5th IFIP WG 2.6 International Symposium, SIMPDA 2015, Vienna, Austria, December 9-11, 2015, Revised Selected Papers

Aus der Reihe Lecture Notes in Business Information Processing

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Beschreibung

This book constitutes the revised selected papers from the 5th IFIP WG 2.6 International Symposium  on Data-Driven Process Discovery and Analysis, SIMPDA 2015, held in Vienna, Austria in December 2015.  The 8 papers presented in this volume were carefully reviewed and selected from 22 submissions. They...

Beschreibung

This book constitutes the revised selected papers from the 5th IFIP WG 2.6 International Symposium  on Data-Driven Process Discovery and Analysis, SIMPDA 2015, held in Vienna, Austria in December 2015. 
The 8 papers presented in this volume were carefully reviewed and selected from 22 submissions. They cover theoretical issues related to process representation, discovery and analysis, or provide practical and operational experiences in process discovery and analysis. They focus mainly on the adoption of process mining algorithms in conjunction and coordination with other techniques and methodologies.

 

Produktdetails

Einband

Taschenbuch
Erscheinungsdatum

28.01.2017
Abbildungen

IX, 185 p. 78 illus.
Herausgeber Paolo Ceravolo + weitere

Produktdetails

Einband

Taschenbuch
Erscheinungsdatum

28.01.2017
Abbildungen

IX, 185 p. 78 illus.
Herausgeber
Verlag Springer
Seitenzahl

185
Maße (L/B/H)

23,5/15,5/1,1 cm
Gewicht

306 g
Auflage

1st ed. 2017
Sprache

Englisch
ISBN

978-3-319-53434-3
Herstelleradresse

Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

Email: ProductSafety@springernature.com

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  • Produktbild: Data-Driven Process Discovery and Analysis

  • A Framework for Safety-critical Process Management in Engineering Projects.- Business Process Reporting Using Process Mining, Analytic Workflows and Process Cubes: A Case Study in Education.- Detecting Changes in Process Behavior Using Comparative Case Clustering.- - Using Domain Knowledge to Enhance Process Mining Results.- - Aligning Process Model Terminology with Hypernym Relations.- Time Series Petri Net Models: Enrichment and Prediction.- Visual Analytics Meets Process Mining: Challenges and Opportunities.- A Relational Data Warehouse for Multidimensional Process Mining.