TY  - BOOK
AU  - Ceravolo,Paolo
AU  - Rinderle-Ma,Stefanie
ED  - SpringerLink (Online service)
TI  - Data-Driven Process Discovery and Analysis: 5th IFIP WG 2.6 International Symposium, SIMPDA 2015, Vienna, Austria, December 9-11, 2015, Revised Selected Papers 
T2  - Lecture Notes in Business Information Processing,
SN  - 9783319534350
AV  - QA76.9.D343 
U1  - 006.312 23
PY  - 2017///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Data mining
KW  - Management information systems
KW  - Industrial management
KW  - Application software
KW  - Data Mining and Knowledge Discovery
KW  - Business Process Management
KW  - Information Systems Applications (incl. Internet)
KW  - Computer Appl. in Administrative Data Processing
N1  - 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.; Available to subscribing member institutions only. Доступно лише організаціям членам підписки
N2  - 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.
UR  - https://doi.org/10.1007/978-3-319-53435-0
ER  -