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020			_a9789811639647
024	7		_a10.1007/978-981-16-3964-7 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9 .D343 _b2021 EB
245	1	0	_aPeriodic Pattern Mining _bTheory, Algorithms, and Applications _cedited by R. Uday Kiran, Philippe Fournier-Viger, Jose M. Luna, Jerry Chun-Wei Lin, Anirban Mondal.
250			_aFirst edition 2021
264		1	_aSingapore _bSpringer International Publising _bSpringer International Publising _c2021.
300			_a1 recurso en línea (VIII, 263 páginas) _b65 ilustraciones, 46 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
490	0		_aComputer Science (SpringerNature-11645)
490	0		_aComputer Science (R0) (SpringerNature-43710)
505	0		_aChapter 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.
520	3		_aThis 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.
988			_aSpringer_Computer_2021
650		7	_2embne _9162648 _aData mining
700	1		_aKiran, R. Uday _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aFournier-Viger, Philippe _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aLuna, Jose M _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aLin, Jerry Chun-Wei _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aMondal, Anirban _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9789811639630
776	0	8	_iPrinted edition: _z9789811639654
776	0	8	_iPrinted edition: _z9789811639661
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-16-3964-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2022 _dz _eh _zSI