This book focuses on the theory, practice, and concepts of process mining techniques in detail, especially pattern recognition in diverse society, science, medicine, engineering, and business. The book deliberates several perspectives on process mining techniques in the broader context of data science and big data approaches.%u3000
Process Mining Techniques for Pattern Recognition: Concepts, Theory, and Practice provides an introduction to process mining techniques and pattern recognition. After that, it delivers the fundamentals of process modelling and mining essential to comprehend the book. The text emphasizes discovery as an important process mining task and includes case studies as well as real-life examples to guide users in successfully applying process mining techniques for pattern recognition in practice.
Intended to be an introduction to process mining and pattern recognition for students, academics, and practitioners, this book is perfect for those who want to learn the basics, and also gain an understanding of the concepts on a deeper level.
Preface
Part I : Introduction to Process Mining Techniques
Chapter 1 : Concepts of Data Mining and Process Mining Chapter 2 : Process Mining Techniques Chapter 3 : Quality Criteria
Part II : Difficulties to Apply Process Mining in Practice
Chapter 4 : Applying Process Mining Techniques to Different Tasks Chapter 5 : Process Mining Techniques : Issues
Part III : Process Mining Techniques for Pattern Recognition
Chapter 6 : Pattern Recognition Chapter 7 : Role of Process Mining Techniques for Pattern Recognition Chapter 8 : Emerging Application and Research Trends Chapter 9 : Future Challenge in Pattern Recognition Chapter 10 : Case Study
