000			04147nam a22004095i 4500
001			285771
003			MX-SnUAN
005			20160429154422.0
007			cr nn 008mamaa
008			150903s2010 xxu| o |||| 0|eng d
020			_a9781441912800 _99781441912800
024	7		_a10.1007/9781441912800 _2doi
035			_avtls000338254
039		9	_a201509030323 _bVLOAD _c201404300342 _dVLOAD _y201402060906 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aHD30.23
100	1		_aStahlbock, Robert. _eeditor. _9314119
245	1	0	_aData Mining : _bSpecial Issue in Annals of Information Systems / _cedited by Robert Stahlbock, Sven F. Crone, Stefan Lessmann.
250			_a1.
264		1	_aBoston, MA : _bSpringer US, _c2010.
300			_axiii, 387 páginas _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aAnnals of Information Systems, _x1934-3221 ; _v8
500			_aSpringer eBooks
505	0		_aData Mining and Information Systems: Quo Vadis? -- Confirmatory data analysis -- Response-Based Segmentation Using Finite Mixture Partial Least Squares -- Knowledge discovery from supervised learning -- Building Acceptable Classification Models -- Mining Interesting Rules Without Support Requirement: A General Universal Existential Upward Closure Property -- Classification Techniques and Error Control in Logic Mining -- Classification analysis -- An Extended Study of the Discriminant Random Forest -- Prediction with the SVM Using Test Point Margins -- Effects of Oversampling Versus Cost-Sensitive Learning for Bayesian and SVM Classifiers -- The Impact of Small Disjuncts on Classifier Learning -- Hybrid data mining procedures -- Predicting Customer Loyalty Labels in a Large Retail Database: A Case Study in Chile -- PCA-based Time Series Similarity Search -- Evolutionary Optimization of Least-Squares Support Vector Machines -- Genetically Evolved kNN Ensembles -- Web-mining -- Behaviorally Founded Recommendation Algorithm for Browsing Assistance Systems -- Using Web Text Mining to Predict Future Events: A Test of the Wisdom of Crowds Hypothesis -- Privacy-preserving data mining -- Avoiding Attribute Disclosure with the (Extended) p-Sensitive k-Anonymity Model -- Privacy-Preserving Random Kernel Classification of Checkerboard Partitioned Data.
520			_aOver the course of the last twenty years, research in data mining has seen a substantial increase in interest, attracting original contributions from various disciplines including computer science, statistics, operations research, and information systems. Data mining supports a wide range of applications, from medical decision making, bioinformatics, web-usage mining, and text and image recognition to prominent business applications in corporate planning, direct marketing, and credit scoring. Research in information systems equally reflects this inter- and multidisciplinary approach, thereby advocating a series of papers at the intersection of data mining and information systems research. This special issue of Annals of Information Systems contains original papers and substantial extensions of selected papers from the 2007 and 2008 International Conference on Data Mining (DMIN’07 and DMIN’08, Las Vegas, NV) that have been rigorously peer-reviewed. The issue brings together topics on both information systems and data mining, and aims to give the reader a current snapshot of the contemporary research and state of the art practice in data mining.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aCrone, Sven F. _eeditor. _9314120
700	1		_aLessmann, Stefan. _eeditor. _9314121
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9781441912794
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-4419-1280-0 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c285771 _d285771