國立虎尾科技大學 |

Next generation of data mining applications

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Next generation of data mining applications/ edited by Mehmed M. Kantardzic, Jozef Zurada.
其他作者:	Kantardzic, Mehmed.
出版者:	Hoboken, N.J. ;Wiley-Interscience, : c2005.,
面頁冊數:	1 online resource (xviii, 671 p.) :ill. :
標題:	Data mining. -
電子資源:	http://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=5769527
電子資源:	http://ieeexplore.ieee.org/servlet/opac?bknumber=5769527
ISBN:	9780471696650

Next generation of data mining applications
Next generation of data mining applications[electronic resource] /edited by Mehmed M. Kantardzic, Jozef Zurada. - Hoboken, N.J. ;Wiley-Interscience,c2005. - 1 online resource (xviii, 671 p.) :ill.

Includes bibliographical references and index.

Trends in data-mining applications : from research labs to fortune 500 companies. -- 1. Mining wafer fabrication : framework and challenges. -- 2. Damage detection employing data-mining techniques. -- 3. Data projection techniques and their application in sensor array data processing. -- 4. An application of evolutionary and neural data-mining techniques to customer relationship management. -- 5. Sales opportunity miner : data mining for automatic evaluation of sales opportunity. -- 6. A fully distributed framework for cost-sensitive data mining. -- 7. Application of variable precision rough set approach to care driver assessment. -- 8. Discovery of patterns in earth science data using data mining. -- 9. An active learning approach to Egeria densa detection in digital imagery. -- 10. Experiences in mining data from computer simulations.

AnnotationThis book presents the next generation of data mining applications based on stateofthe art methodologies and techniques for analyzing enormous quantities of raw data in highdimension Each chapter describes the data mining development process, results, and experiences with new data mining tools and techniques Includes twentyfive novel and diverse contributions from experienced and wellrespected data mining scientists and practitioners that describe their recent applications using stateoftheart methods and algorithms.

ISBN: 9780471696650

Source: 9780471696650IEEEhttp://ieeexplore.ieee.orgSubjects--Topical Terms:

528622
Data mining.
Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: QA76.9.D343 / N49 2005

Dewey Class. No.: 006.3/12

Next generation of data mining applications
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245 0 0 $a Next generation of data mining applications $h [electronic resource] / $c edited by Mehmed M. Kantardzic, Jozef Zurada.
260 $a Hoboken, N.J. ; $a [Great Britain] : $b Wiley-Interscience, $c c2005.
300 $a 1 online resource (xviii, 671 p.) : $b ill.
504 $a Includes bibliographical references and index.
505 0 $a Trends in data-mining applications : from research labs to fortune 500 companies. -- 1. Mining wafer fabrication : framework and challenges. -- 2. Damage detection employing data-mining techniques. -- 3. Data projection techniques and their application in sensor array data processing. -- 4. An application of evolutionary and neural data-mining techniques to customer relationship management. -- 5. Sales opportunity miner : data mining for automatic evaluation of sales opportunity. -- 6. A fully distributed framework for cost-sensitive data mining. -- 7. Application of variable precision rough set approach to care driver assessment. -- 8. Discovery of patterns in earth science data using data mining. -- 9. An active learning approach to Egeria densa detection in digital imagery. -- 10. Experiences in mining data from computer simulations.
505 0 $a 11. Statistical modeling of large-scale scientific simulation data. -- 12. Data mining for gene mapping. -- 13. Data-mining techniques for microarray data analysis. -- 14. The use of emerging patterns in the analysis of gene expression profiles for the diagnosis and understanding of diseases. -- 15. Proteomic data analysis : pattern recognition for medical diagnosis and biomarker discovery. -- 16. Discovering patterns and reference models in the medical domain of isokinetics. -- 17. Mining the cystic fibrosis data. -- 18. On learning strategies for topic-specific web crawling. -- 19. On analyzing web log data : a parallel sequence-mining algorithm. -- 20. Interactive methods for taxonomy editing and validation. -- 21. The use of data-mining techniques in operational crime fighting. -- 22 .Using data mining for intrusion detection. -- 23. Mining closed and maximal frequent itemsets. -- 24. Using fractals in data mining. -- 25 .Genetic search for logic structures in data.
520 8 $a Annotation $b This book presents the next generation of data mining applications based on stateofthe art methodologies and techniques for analyzing enormous quantities of raw data in highdimension Each chapter describes the data mining development process, results, and experiences with new data mining tools and techniques Includes twentyfive novel and diverse contributions from experienced and wellrespected data mining scientists and practitioners that describe their recent applications using stateoftheart methods and algorithms.
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700 1 $a Kantardzic, Mehmed. $3 772495
700 1 $a Zurada, Jozef, $d 1949- $3 881130
856 4 0 $3 IEEE Xplore $u http://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=5769527
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