000			05272nam a22004935i 4500
001			978-0-387-69935-6
003			DE-He213
005			20250710084010.0
007			cr nn 008mamaa
008			100301s2008 xxu| s |||| 0|eng d
020			_a9780387699356 _a99780387699356
024	7		_a10.1007/978-0-387-69935-6 _2doi
082	0	4	_a005.74 _223
100	1		_aMaimon, Oded. _eeditor.
245	1	0	_aSoft Computing for Knowledge Discovery and Data Mining _h[recurso electrónico] / _cedited by Oded Maimon, Lior Rokach.
264		1	_aBoston, MA : _bSpringer US, _c2008.
300			_bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aNeural Network Methods -- to Soft Computing for Knowledge Discovery and Data Mining -- Neural Networks For Data Mining -- Improved SOM Labeling Methodology for Data Mining Applications -- Evolutionary Methods -- A Review of evolutionary Algorithms for Data Mining -- Genetic Clustering for Data Mining -- Discovering New Rule Induction Algorithms with Grammar-based Genetic Programming -- evolutionary Design of Code-matrices for Multiclass Problems -- Fuzzy Logic Methods -- The Role of Fuzzy Sets in Data Mining -- Support Vector Machines and Fuzzy Systems -- KDD in Marketing with Genetic Fuzzy Systems -- Knowledge Discovery in a Framework for Modelling with Words -- Advanced Soft Computing Methods and Areas -- Swarm Intelligence Algorithms for Data Clustering -- A Diffusion Framework for Dimensionality Reduction -- Data Mining and Agent Technology: a fruitful symbiosis -- Approximate Frequent Itemset Mining In the Presence of Random Noise -- The Impact of Overfitting and Overgeneralization on the Classification Accuracy in Data Mining.
520			_aData mining is the science and technology of exploring large and complex bodies of data in order to discover useful and insightful patterns. It is extremely important because it enables modeling and knowledge extraction from abundant data availability. Soft Computing for Knowledge Discovery and Data Mining introduces theoretical approaches and practical computing methods extending the envelope of problems that data mining can solve efficiently. From the editors of the leading Data Mining and Knowledge Discovery Handbook, 2005, this volume, by highly regarded authors, includes selected contributors of the Handbook. The first three parts of this book are devoted to the principal constituents of soft computing: neural networks, evolutionary algorithms and fuzzy logic. The last part compiles the recent advances in soft computing for data mining, such as swarm intelligence, diffusion process and agent technology. This book was written to provide investigators in the fields of information systems, engineering, computer science, operations research, bio-informatics, statistics and management with a profound source for the role of soft computing in data mining. Not only does this book feature illustrations of various applications including marketing, manufacturing, medical, and others, but it also includes various real-world case studies with detailed results. Soft Computing for Knowledge Discovery and Data Mining is designed for theoreticians, researchers and advanced practitioners in industry. Practitioners may be particularly interested in the description of real world data mining projects performed with soft computing. This book is also suitable as a textbook or reference for advanced-level students in mathematical quantitative methods in the above fields. About the editors: Oded Maimon is Full Professor at the Department of Industrial Engineering, Tel-Aviv University, Israel. Lior Rokach is Assistant Professor at the Department of Information System Engineering, Ben-Gurion University of the Negev, Israel. Maimon and Rokach are recognized international experts in data mining and business intelligence, and serve in leading positions in this field. They have written numerous scientific articles and are the editors of the complete Data Mining and Knowledge Discovery Handbook (2005). They have jointly authored two of the best detailed books in the field of data mining: Decomposition Methodology for Knowledge Discovery and Data Mining (2005), and Data Mining with Decision Trees (2007).
650		0	_aCOMPUTER SCIENCE.
650		0	_aCOMPUTER COMMUNICATION NETWORKS.
650		0	_aDATABASE MANAGEMENT.
650		0	_aINFORMATION STORAGE AND RETRIEVAL SYSTEMS.
650		0	_aINFORMATION SYSTEMS.
650		0	_aOPTICAL PATTERN RECOGNITION.
650	1	4	_aCOMPUTER SCIENCE.
650	2	4	_aDATABASE MANAGEMENT.
650	2	4	_aINFORMATION STORAGE AND RETRIEVAL.
650	2	4	_aPATTERN RECOGNITION.
650	2	4	_aCOMPUTER COMMUNICATION NETWORKS.
650	2	4	_aINFORMATION SYSTEMS APPLICATIONS (INCL.INTERNET).
700	1		_aRokach, Lior. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387699349
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-69935-6 _zVer el texto completo en las instalaciones del CICY
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