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Periodic Pattern Mining = Theory, Algorithms, and Applications /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Periodic Pattern Mining / edited by R. Uday Kiran, Philippe Fournier-Viger, Jose M. Luna, Jerry Chun-Wei Lin, Anirban Mondal.
其他題名:	Theory, Algorithms, and Applications /
其他作者:	Kiran, R. Uday.
面頁冊數:	VIII, 263 p. 65 illus., 46 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Artificial intelligence. -
電子資源:	https://doi.org/10.1007/978-981-16-3964-7
ISBN:	9789811639647

Periodic Pattern Mining = Theory, Algorithms, and Applications /
Periodic Pattern Mining Theory, Algorithms, and Applications /[electronic resource] :edited by R. Uday Kiran, Philippe Fournier-Viger, Jose M. Luna, Jerry Chun-Wei Lin, Anirban Mondal. - 1st ed. 2021. - VIII, 263 p. 65 illus., 46 illus. in color.online resource.

Chapter 1: Introduction to Data Mining -- Chapter 2: Discovering Frequent Patterns in Very Large Transactional Database -- Chapter 3: Discovering Periodic Frequent Patterns in Temporal Databases -- Chapter 4: Discovering Fuzzy Periodic Frequent Patterns in Quantitative Temporal Databases -- Chapter 5: Discovering Partial Periodic Patterns in Temporal Databases -- Chapter 6: Finding Periodic Patterns in Multiple Sequences -- Chapter 7: Discovering Self Reliant Patterns -- Chapter 8: Finding Periodic High Utility Patterns in Sequence -- Chapter 9: Mining Periodic High Utility Sequential Patterns with Negative Unit Profits -- Chapter 10: Hiding Periodic High Utility Sequential Patterns -- Chapter 11: NetHAPP -- Chapter 12: Privacy Preservation of Periodic Frequent Patterns using Sensitive Inverse Frequency.

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.

ISBN: 9789811639647

Standard No.: 10.1007/978-981-16-3964-7doiSubjects--Topical Terms:

559380
Artificial intelligence.

LC Class. No.: Q334-342

Dewey Class. No.: 006.3

Periodic Pattern Mining = Theory, Algorithms, and Applications /
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