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The Resource Next generation of data mining applications, edited by Mehmed M. Kantardzic, Jozef Zurada, (electronic resource)

Next generation of data mining applications, edited by Mehmed M. Kantardzic, Jozef Zurada, (electronic resource)

Work
Publication
Extent
1 online resource (xviii, 671 p.)
Note
Made available via IEEE Xplore Digital Library
Contents
  • 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
  • 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
Isbn
9780471656050
Instance
Label
Next generation of data mining applications
Title
Next generation of data mining applications
Statement of responsibility
edited by Mehmed M. Kantardzic, Jozef Zurada
Contributor
Provider
Publisher
Subject
Language
eng
Summary
Annotation
Cataloging source
LLB
Illustrations
illustrations
Index
index present
LC call number
QA76.9.D343
LC item number
N49 2005
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorDate
1949-
http://library.link/vocab/relatedWorkOrContributorName
  • Kantardzic, Mehmed
  • Zurada, Jozef
  • IEEE Xplore
  • John Wiley & Sons
  • Institute of Electrical and Electronics Engineers
http://library.link/vocab/subjectName
  • Data mining
  • Exploration de données (Informatique)
  • Data Mining
Summary expansion
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
Label
Next generation of data mining applications, edited by Mehmed M. Kantardzic, Jozef Zurada, (electronic resource)
Instantiates
Publication
Note
Made available via IEEE Xplore Digital Library
Bibliography note
Includes bibliographical references and index
Color
multicolored
Contents
  • 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
  • 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
Dimensions
unknown
Extent
1 online resource (xviii, 671 p.)
Form of item
online
Isbn
9780471656050
Other physical details
ill.
Specific material designation
remote
Stock number
9780471696650
System control number
  • (OCoLC)728165217
  • (OCoLC)ocn728165217
Label
Next generation of data mining applications, edited by Mehmed M. Kantardzic, Jozef Zurada, (electronic resource)
Publication
Note
Made available via IEEE Xplore Digital Library
Bibliography note
Includes bibliographical references and index
Color
multicolored
Contents
  • 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
  • 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
Dimensions
unknown
Extent
1 online resource (xviii, 671 p.)
Form of item
online
Isbn
9780471656050
Other physical details
ill.
Specific material designation
remote
Stock number
9780471696650
System control number
  • (OCoLC)728165217
  • (OCoLC)ocn728165217

Subject

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