ISBN: 9789811639630 - periodic pattern mining: theory, algorithms, and applications (14 resultados)

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  • Idioma: Inglés

    Editorial: Springer, 2021

    9811639639 / 9789811639630

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    Editorial: Springer, 2021

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    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

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  • Idioma: Inglés

    Editorial: Springer, 2021

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    Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK

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  • Idioma: Inglés

    Editorial: Springer, 2021

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Buch. Condición: 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.…

  • Idioma: Inglés

    Editorial: Springer, 2021

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    Librería: Books Puddle, Woodside, NY, Estados Unidos de AmericaBooks Puddle

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    Condición: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.

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    Hardcover. Condición: Brand New. 271 pages. 9.25x6.10x1.93 inches. In Stock.

  • Idioma: Inglés

    Editorial: Springer, 2021

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    Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand

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  • Idioma: Inglés

    Editorial: Springer Nature Singapore Okt 2021, 2021

    9811639639 / 9789811639630

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 272 pp. Englisch.…

  • Idioma: Inglés

    Editorial: Springer, Berlin|Springer Nature Singapore|Springer, 2021

    9811639639 / 9789811639630

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    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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.This book provides an introduction to the field of periodic pattern mining, revi.…

  • Idioma: Inglés

    Editorial: Springer, Springer Okt 2021, 2021

    9811639639 / 9789811639630

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    Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 272 pp. Englisch.…

  • Idioma: Inglés

    Editorial: Springer, 2021

    9811639639 / 9789811639630

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    Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books

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  • Idioma: Inglés

    Editorial: Springer, 2021

    9811639639 / 9789811639630

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    Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios

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