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170203 ||| eng |
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|a 9783319534350
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| 100 |
1 |
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|a Ceravolo, Paolo
|e [editor]
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| 245 |
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|a Data-Driven Process Discovery and Analysis
|h Elektronische Ressource
|b 5th IFIP WG 2.6 International Symposium, SIMPDA 2015, Vienna, Austria, December 9-11, 2015, Revised Selected Papers
|c edited by Paolo Ceravolo, Stefanie Rinderle-Ma
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| 250 |
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|a 1st ed. 2017
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2017, 2017
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| 300 |
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|a IX, 185 p. 78 illus
|b online resource
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| 505 |
0 |
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|a 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.
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| 653 |
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|a Data mining
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| 653 |
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|a Application software
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| 653 |
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|a Computer Application in Administrative Data Processing
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| 653 |
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|a Data Mining and Knowledge Discovery
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| 653 |
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|a Business Process Management
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| 653 |
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|a Computer and Information Systems Applications
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| 653 |
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|a Information technology / Management
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| 700 |
1 |
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|a Rinderle-Ma, Stefanie
|e [editor]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Lecture Notes in Business Information Processing
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| 028 |
5 |
0 |
|a 10.1007/978-3-319-53435-0
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-319-53435-0?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 006.312
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| 520 |
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|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.
|