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High-Utility Pattern Mining

Cover von High-Utility Pattern Mining

Theory, Algorithms and Applications, Studies in Big Data 51

Philippe Fournier-Viger/Jerry Chun-Wei Lin/Roger Nkambou et al

Springer Verlag GmbH

106.99

(inklusive MwSt.)

Verfügbarkeit: Besorgungstitel, Festbezug

Zusatztext

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.

Weitere Details

Erschienen: 31.01.2019

Umfang: viii, 337 S., 44 s/w Illustr., 79 farbige Illustr.

Sprache: ENG

Einband: GEB

ISBN/EAN: 9783030049201

Umbreit-Nr.: 5785235

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