000 08852nam a2201789 i 4500
001 5769527
003 IEEE
005 20220712205800.0
006 m o d
007 cr |n|||||||||
008 151221s2005 njua ob 001 eng d
010 _z 2005277335 (print)
020 _a9780471696650
_qelectronic
020 _z9780471656050
_qprint
020 _z0471656054
_qpaper
020 _z047169665X
_qelectronic
024 7 _a10.1109/9780471696650
_2doi
035 _a(CaBNVSL)mat05769527
035 _a(IDAMS)0b000064815400e8
040 _aCaBNVSL
_beng
_erda
_cCaBNVSL
_dCaBNVSL
050 4 _aQA76.9.D343
_bN49 2005eb
082 0 4 _a006.3/12
_223
245 0 0 _aNext generation of data mining applications /
_cedited by Mehmed M. Kantardzic, Jozef Zurada.
264 1 _aHoboken, New Jersey :
_bWiley-Interscience,
_cc2005.
264 2 _a[Piscataqay, New Jersey] :
_bIEEE Xplore,
_c[2005]
300 _a1 PDF (xviii, 671 pages) :
_billustrations.
336 _atext
_2rdacontent
337 _aelectronic
_2isbdmedia
338 _aonline resource
_2rdacarrier
504 _aIncludes bibliographical references and index.
505 0 _aTrends 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.
506 1 _aRestricted to subscribers or individual electronic text purchasers.
520 _aDiscover the next generation of data-mining tools and technologyThis book brings together an international team of eighty experts to present readers with the next generation of data-mining applications. Unlike other publications that take a strictly academic and theoretical approach, this book features authors who have successfully developed data-mining solutions for a variety of customer types. Presenting their state-of-the-art methodologies and techniques, the authors show readers how they can analyze enormous quantities of data and make new discoveries by connecting key pieces of data that may be spread across several different databases and file servers. The latest data-mining techniques that will revolutionize research across a wide variety of fields including business, science, healthcare, and industry are all presented. Organized by application, the twenty-five chapters cover applications in:. Industry and business . Science and engineering . Bioinformatics and biotechnology . Medicine and pharmaceuticals. Web and text-mining . Security. New trends in data-mining technology. And much more . . .Readers from a variety of disciplines will learn how the next generation of data-mining applications can radically enhance their ability to analyze data and open the doors to new opportunities. Readers will discover:. New data-mining tools to automate the evaluation and qualification of sales opportunities. The latest tools needed for gene mapping and proteomic data analysis. Sophisticated techniques that can be engaged in crime fighting and preventionWith its coverage of the most advanced applications, Next Generation of Data-Mining Applications is essential reading for all researchers working in data mining or who are tasked with making sense of an ever-growing quantity of data. The publication also serves as an excellent textbook for upper-level undergraduate and graduate courses in computer science, information management, and statistics.
530 _aAlso available in print.
538 _aMode of access: World Wide Web
588 _aDescription based on PDF viewed 12/21/2015.
650 0 _aData mining.
_93907
655 0 _aElectronic books.
_93294
695 _aData models
695 _aData visualization
695 _aDatabases
695 _aDecision trees
695 _aDelta modulation
695 _aDiseases
695 _aDistributed databases
695 _aDriver circuits
695 _aDrugs
695 _aEarth
695 _aElectronic noses
695 _aElectronics packaging
695 _aFabrication
695 _aFeedback loop
695 _aFiltering
695 _aFinite element methods
695 _aFocusing
695 _aFourier transforms
695 _aFractals
695 _aFuel cells
695 _aFuzzy logic
695 _aGene expression
695 _aGenerators
695 _aGenetics
695 _aGenomics
695 _aHistory
695 _aHumans
695 _aIP networks
695 _aIndexes
695 _aInjuries
695 _aInsurance
695 _aIntegrated circuits
695 _aIntrusion detection
695 _aItemsets
695 _aJoining processes
695 _aJoints
695 _aKernel
695 _aLattices
695 _aManuals
695 _aMarketing and sales
695 _aMarkov processes
695 _aMathematical model
695 _aMeasurement
695 _aMeteorology
695 _aMetrology
695 _aNeurons
695 _aNext generation networking
695 _aNiobium
695 _aNose
695 _aOcean temperature
695 _aPartitioning algorithms
695 _aPeriodic structures
695 _aPipelines
695 _aPoles and towers
695 _aPrediction algorithms
695 _aPredictive models
695 _aProbabilistic logic
695 _aProduction
695 _aProgram processors
695 _aProteins
695 _aProteomics
695 _aRNA
695 _aSafety
695 _aSearch problems
695 _aSections
695 _aSecurity
695 _aShape
695 _aSilicon
695 _aSoftware algorithms
695 _aSupport vector machine classification
695 _aSupport vector machines
695 _aTaxonomy
695 _aTesting
695 _aTime series analysis
695 _aTraining
695 _aWeb pages
695 _aWeb sites
695 _aAccidents
695 _aAlgorithm design and analysis
695 _aAnalytical models
695 _aApproximation methods
695 _aArrays
695 _aArtificial intelligence
695 _aArtificial neural networks
695 _aAtmospheric modeling
695 _aBiographies
695 _aBioinformatics
695 _aBiological cells
695 _aBiotechnology
695 _aBuildings
695 _aBusiness
695 _aCities and towns
695 _aClassification algorithms
695 _aCleaning
695 _aClustering algorithms
695 _aCommunities
695 _aCompanies
695 _aComputational modeling
695 _aComputer simulation
695 _aCorrelation
695 _aCouplings
695 _aCrawlers
695 _aCredit cards
695 _aDNA
695 _aData analysis
695 _aData mining
700 1 _aZurada, Jozef,
_d1949-
_927675
700 1 _aKantardzic, Mehmed.
_927676
710 2 _aJohn Wiley & Sons,
_epublisher.
_96902
710 2 _aIEEE Xplore (Online service),
_edistributor.
_927677
776 0 8 _iPrint version:
_z9780471656050
856 4 2 _3Abstract with links to resource
_uhttps://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=5769527
942 _cEBK
999 _c74137
_d74137