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020			_a9780387294896 _99780387294896
024	7		_a10.1007/9780387294896 _2doi
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040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQA76.9.D343
100	1		_aVaidya, Jaideep. _eautor _9300271
245	1	0	_aPrivacy Preserving Data Mining / _cby Jaideep Vaidya, Yu Michael Zhu, Christopher W. Clifton.
264		1	_aBoston, MA : _bSpringer US, _c2006.
300			_ax, 121 páginas, 20 ilustraciones _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		_aAdvances in Information Security, _x1568-2633 ; _v19
500			_aSpringer eBooks
505	0		_aPrivacy and Data Mining -- What is Privacy? -- Solution Approaches / Problems -- Predictive Modeling for Classification -- Predictive Modeling for Regression -- Finding Patterns and Rules (Association Rules) -- Descriptive Modeling (Clustering, Outlier Detection) -- Future Research - Problems remaining.
520			_aData mining has emerged as a significant technology for gaining knowledge from vast quantities of data. However, concerns are growing that use of this technology can violate individual privacy. These concerns have led to a backlash against the technology, for example, a "Data-Mining Moratorium Act" introduced in the U.S. Senate that would have banned all data-mining programs (including research and development) by the U.S. Department of Defense. Privacy Preserving Data Mining provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. This book demonstrates how these approaches can achieve data mining, while operating within legal and commercial restrictions that forbid release of data. Furthermore, this research crystallizes much of the underlying foundation, and inspires further research in the area. Privacy Preserving Data Mining is designed for a professional audience composed of practitioners and researchers in industry. This volume is also suitable for graduate-level students in computer science.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aZhu, Yu Michael. _eautor _9300272
700	1		_aClifton, Christopher W. _eautor _9300273
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9780387258867
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-0-387-29489-6 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c277469 _d277469