Details
High-Utility Pattern Mining
Theory, Algorithms and ApplicationsStudies in Big Data, Band 51
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96,29 € |
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| Verlag: | Springer |
| Format: | |
| Veröffentl.: | 18.01.2019 |
| ISBN/EAN: | 9783030049218 |
| Sprache: | englisch |
Dieses eBook enthält ein Wasserzeichen.
Beschreibungen
<p>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.</p>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.<p></p>
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Introduction.- Problem Definition.- Algorithms.- Extensions of the Problem.- Research Opportunities.- Open-Source Implementations.- Conclusion.
<p>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.</p>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.<p></p>
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Presents an overview of the theory and core methods used in utility mining Covers recent advances in high-utility mining Includes stream, incremental, sequence, and big data mining Discusses important applications and open-source software
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