Process Mining Techniques in Business Environments: Theoretical Aspects, Algorithms, Techniques and Open Challenges in Process Mining
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.
Chapter 1 Introduction
Part I State of the Art: BPM, Data Miningand Process Mining
Chapter 2 Introduction to Business Processes, BPM, and BPM Systems
Chapter 3 Data Generated by Information Systems (and How to Get It)
Chapter 4 Data Mining for Information System Data
Chapter 5 Process Mining
Chapter 6 Quality Criteria in Process Mining
Chapter 7 Event Streams
Part II Obstacles to Process Mining in Practice
Chapter 8 Obstacles to Applying Process Mining in Practice
Chapter 9 Long-Term View Scenario
Part III Process Mining as an EmergingTechnology
Chapter 10 Data Preparation
Chapter 11 Heuristics Miner for Time Interval
Chapter 12 Automatic Configuration of Mining Algorithm
Chapter 13 User-Guided Discovery of Process Models
Chapter 14 Extensions of Business Processes with Organizational Roles
Chapter 15 Results Interpretation and Evaluation
Chapter 16 Hands-On: Obtaining Test Data
Part IV A New Challenge in Process Mining
Chapter 17 Process Mining for Stream Data Sources
Part V Conclusions and Future Work
Chapter 18 Conclusions and Future Work
