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

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. The...

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Corporate Author: SpringerLink (Online service)
Other Authors: Ceravolo, Paolo (Editor), Rinderle-Ma, Stefanie (Editor)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2017, 2017
Edition:1st ed. 2017
Series:Lecture Notes in Business Information Processing
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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505 0 |a 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. 
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653 |a Information Systems Applications (incl. Internet) 
653 |a Business Process Management 
653 |a Computer Appl. in Administrative Data Processing 
653 |a Data mining 
653 |a Application software 
653 |a Data Mining and Knowledge Discovery 
653 |a Industrial management 
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520 |a 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.