Can I read High-Utility Pattern Mining: Theory, Algorithms and Applications (Studies in Big Data Book 51) on EtoBox?

High-Utility Pattern Mining: Theory, Algorithms and Applications (Studies in Big Data Book 51) by Philippe Fournier-Viger, Jerry Chun-Wei Lin, Roger Nkambou, Bay Vo, Vincent S. Tseng is a nonfiction available to read on EtoBox.

What is High-Utility Pattern Mining: Theory, Algorithms and Applications (Studies in Big Data Book 51) about?

"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." -- prové de l'editor

Who reads High-Utility Pattern Mining: Theory, Algorithms and Applications (Studies in Big Data Book 51)?

Author

Philippe Fournier-Viger, Jerry Chun-Wei Lin, Roger Nkambou, Bay Vo, Vincent S. Tseng

Publisher

Springer International Publishing : Imprint: Springer

Published

2019

Language

EN

ISBN

9783030049201

Category

nonfiction

Subjects

Computer Science, Science, Engineering

Updated

2026-03-24