This book investigates the theory, algorithms, and applications of discovering high-utility patterns within data. It provides a comprehensive overview of techniques for identifying patterns that hold significant importance, covering various types of high-utility patterns and the fundamental algorithms used for their extraction. The text also details recent advancements, practical applications, available open-source software, and potential avenues for future research, with a focus on discrete data types such as customer transactions and sequential data.

This book is positioned as a comprehensive resource for understanding high-utility pattern mining. The structure, with dedicated survey chapters and application-focused sections, suggests it aims to serve both as an introductory text and a reference for researchers. The inclusion of diverse topics like privacy-preserving mining and pattern visualization indicates a broad scope intended to cover the multifaceted nature of the field.