Process Mining Techniques in Business Environments
Theoretical Aspects, Algorithms, Techniques and Open Challenges in Process Mining
Published on 15. May 2015
Book
Paperback/Softback
XII, 220 pages
978-3-319-17481-5 (ISBN)
Description
After a brief presentation of the state of the art of process-mining techniques, Andrea Burratin proposes different scenarios for the deployment of process-mining projects, and in particular a characterization of companies in terms of their process awareness. The approaches proposed in this book belong to two different computational paradigms: first to classic "batch process mining," and second to more recent "online process mining."
The book encompasses a revised version of the author's PhD thesis, which won the "Best Process Mining Dissertation Award" in 2014, awarded by the IEEE Task Force on Process Mining.More details
Series
Edition
2015 ed.
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Research
Illustrations
101 s/w Abbildungen
XII, 220 p. 101 illus.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 13 mm
Weight
359 gr
ISBN-13
978-3-319-17481-5 (9783319174815)
DOI
10.1007/978-3-319-17482-2
Schweitzer Classification
Other editions
Additional editions
Andrea Burattin
Process Mining Techniques in Business Environments
Theoretical Aspects, Algorithms, Techniques and Open Challenges in Process Mining
E-Book
05/2015
Springer
€64.19
Available for download
Content
1 Introduction.- Part I: State of the Art: BPM, Data Mining and Process Mining.- 2 Introduction to Business Processes, BPM, and BPM Systems.- 3 Data Generated by Information Systems (and How to Get It).- 4 Data Mining for Information System Data.- 5 Process Mining.- 6 Quality Criteria in Process Mining.- 7 Event Streams.- Part II: Obstacles to Process Mining in Practice.- 8 Obstacles to Applying Process Mining in Practice.- 9 Long-term View Scenario.- Part III: Process Mining as an Emerging Technology.- 10 Data Preparation.- 11 Heuristics Miner for Time Interval.- 12 Automatic Configuration of Mining Algorithm.- 13 User-Guided Discovery of Process Models.- 14 Extensions of Business Processes with Organizational Roles.- 15 Results Interpretation and Evaluation.- 16 Hands-On: Obtaining Test Data.- Part IV: A New Challenge in Process Mining.- 17 Process Mining for Stream Data Sources.- Part V: Conclusions and Future Work.- 18 Conclusions and Future Work.