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Data-driven process discovery and an...
~
Rinderle-Ma, Stefanie.
Data-driven process discovery and analysis = 5th IFIP WG 2.6 International Symposium, SIMPDA 2015, Vienna, Austria, December 9-11, 2015 : revised selected papers /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Data-driven process discovery and analysis/ edited by Paolo Ceravolo, Stefanie Rinderle-Ma.
Reminder of title:
5th IFIP WG 2.6 International Symposium, SIMPDA 2015, Vienna, Austria, December 9-11, 2015 : revised selected papers /
remainder title:
SIMPDA 2015
other author:
Ceravolo, Paolo.
corporate name:
Workshop on the Preservation of Stability under Discretization
Published:
Cham :Springer International Publishing : : 2017.,
Description:
ix, 185 p. :ill., digital ; : 24 cm.;
Contained By:
Springer eBooks
Subject:
Data mining - Congresses. -
Online resource:
http://dx.doi.org/10.1007/978-3-319-53435-0
ISBN:
9783319534350
Data-driven process discovery and analysis = 5th IFIP WG 2.6 International Symposium, SIMPDA 2015, Vienna, Austria, December 9-11, 2015 : revised selected papers /
Data-driven process discovery and analysis
5th IFIP WG 2.6 International Symposium, SIMPDA 2015, Vienna, Austria, December 9-11, 2015 : revised selected papers /[electronic resource] :SIMPDA 2015edited by Paolo Ceravolo, Stefanie Rinderle-Ma. - Cham :Springer International Publishing :2017. - ix, 185 p. :ill., digital ;24 cm. - Lecture notes in business information processing,2441865-1348 ;. - Lecture notes in business information processing ;134..
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.
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.
ISBN: 9783319534350
Standard No.: 10.1007/978-3-319-53435-0doiSubjects--Topical Terms:
528575
Data mining
--Congresses.
LC Class. No.: QA76.9.D343
Dewey Class. No.: 006.312
Data-driven process discovery and analysis = 5th IFIP WG 2.6 International Symposium, SIMPDA 2015, Vienna, Austria, December 9-11, 2015 : revised selected papers /
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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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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.
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