High-Utility Pattern Mining : Theory, Algorithms and Applications
Language: English
Published by Springer, 2019
- Hardcover
- Used
Condition: Used
US$ 101.98
Quantity: 1 available
Add to basketItem description from seller
Zustand: Hervorragend | Seiten: 348 | Sprache: Englisch | Produktart: Bücher | 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.
Seller Inventory # 33274403/1
- Title
- High-Utility Pattern Mining : Theory, Algorithms and Applications
- Author
- Unbekannt
- Publisher
- Springer
- Publication year
- 2019
- Condition
- Hervorragend
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3030049205
- ISBN 13
- 9783030049201
- Series
- Book 45 of 95: Studies in Big Data
- Seller catalogs
- Bücher
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.
"Synopsis" may belong to another edition of this title.
From the Back Cover
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.
"About the title" may belong to another edition of this title.
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