This book presents an overview of techniques for discovering high-utility patterns (patterns
with a high importance) in data. It introduces the main types of high-utility patterns as well
as the theory and core algorithms for high-utility pattern mining and describes recent
advances applications open-source software and research opportunities. It also discusses
several types of discrete data including customer transaction data and sequential data.The
book consists of twelve chapters seven of which are surveys presenting the main subfields of
high-utility pattern mining including itemset mining sequential pattern mining big data
pattern mining metaheuristic-based approaches privacy-preserving pattern mining and pattern
visualization. The remaining five chapters describe key techniques and applications such as
discovering concise representations and regular patterns.
