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Periodic Pattern Mining : Theory, Algorithms, and Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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£ 128.81
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Periodic Pattern Mining: Theory, Algorithms, and Applications
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Periodic Pattern Mining: Theory, Algorithms, and Applications
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Periodic Pattern Mining : Theory, Algorithms, and Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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£ 138.32
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Periodic Pattern Mining : Theory, Algorithms, and Applications
Published by Springer Nature Singapore, Springer Nature Singapore, 2022
ISBN 10: 9811639663 ISBN 13: 9789811639661
Language: English
£ 145.43
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an introduction to the field of periodic pattern mining, reviews state-of-the-art techniques, discusses recent advances, and reviews open-source software. Periodic pattern mining is a popular and emerging research area in the field of data mining. It involves discovering all regularly occurring patterns in temporal databases. One of the major applications of periodic pattern mining is the analysis of customer transaction databases to discover sets of items that have been regularly purchased by customers. Discovering such patterns has several implications for understanding the behavior of customers. Since the first work on periodic pattern mining, numerous studies have been published and great advances have been made in this field. The book consists of three main parts: introduction, algorithms, and applications.The first chapter is an introduction to pattern mining and periodic pattern mining. The concepts of periodicity, periodic support, search space exploration techniques, and pruning strategies are discussed. The main types of algorithms are also presented such as periodic-frequent pattern growth, partial periodic pattern-growth, and periodic high-utility itemset mining algorithm. Challenges and research opportunities are reviewed.The chapters that follow present state-of-the-art techniques for discovering periodic patterns in (1) transactional databases, (2) temporal databases, (3) quantitative temporal databases, and (4) big data. Then, the theory on concise representations of periodic patterns is presented, as well as hiding sensitive information using privacy-preserving data mining techniques.The book concludes with several applications of periodic pattern mining, including applications in air pollution data analytics, accident data analytics, and traffic congestion analytics.
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£ 145
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Periodic Pattern Mining : Theory, Algorithms, and Applications
Published by Springer Nature Singapore, Springer Nature Singapore, 2021
ISBN 10: 9811639639 ISBN 13: 9789811639630
Language: English
£ 146.84
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Add to basketBuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an introduction to the field of periodic pattern mining, reviews state-of-the-art techniques, discusses recent advances, and reviews open-source software. Periodic pattern mining is a popular and emerging research area in the field of data mining. It involves discovering all regularly occurring patterns in temporal databases. One of the major applications of periodic pattern mining is the analysis of customer transaction databases to discover sets of items that have been regularly purchased by customers. Discovering such patterns has several implications for understanding the behavior of customers. Since the first work on periodic pattern mining, numerous studies have been published and great advances have been made in this field. The book consists of three main parts: introduction, algorithms, and applications.The first chapter is an introduction to pattern mining and periodic pattern mining. The concepts of periodicity, periodic support, search space exploration techniques, and pruning strategies are discussed. The main types of algorithms are also presented such as periodic-frequent pattern growth, partial periodic pattern-growth, and periodic high-utility itemset mining algorithm. Challenges and research opportunities are reviewed.The chapters that follow present state-of-the-art techniques for discovering periodic patterns in (1) transactional databases, (2) temporal databases, (3) quantitative temporal databases, and (4) big data. Then, the theory on concise representations of periodic patterns is presented, as well as hiding sensitive information using privacy-preserving data mining techniques.The book concludes with several applications of periodic pattern mining, including applications in air pollution data analytics, accident data analytics, and traffic congestion analytics.
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Add to basketCondition: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
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Paperback. Condition: Brand New. 271 pages. 9.25x6.10x0.75 inches. In Stock.
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