000 | 08812nam a2201789 i 4500 | ||
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001 | 5769527 | ||
003 | IEEE | ||
005 | 20200421114119.0 | ||
006 | m o d | ||
007 | cr |n||||||||| | ||
008 | 151221s2005 njua ob 001 eng d | ||
010 | _z 2005277335 (print) | ||
020 |
_a9780471696650 _qelectronic |
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020 |
_z9780471656050 _qprint |
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020 |
_z0471656054 _qpaper |
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020 |
_z047169665X _qelectronic |
||
024 | 7 |
_a10.1109/9780471696650 _2doi |
|
035 | _a(CaBNVSL)mat05769527 | ||
035 | _a(IDAMS)0b000064815400e8 | ||
040 |
_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL |
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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. |
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264 | 2 |
_a[Piscataqay, New Jersey] : _bIEEE Xplore, _c[2005] |
|
300 |
_a1 PDF (xviii, 671 pages) : _billustrations. |
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336 |
_atext _2rdacontent |
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337 |
_aelectronic _2isbdmedia |
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338 |
_aonline resource _2rdacarrier |
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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. | |
655 | 0 | _aElectronic books. | |
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 | ||
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 | ||
700 | 1 |
_aZurada, Jozef, _d1949- |
|
700 | 1 | _aKantardzic, Mehmed. | |
710 | 2 |
_aJohn Wiley & Sons, _epublisher. |
|
710 | 2 |
_aIEEE Xplore (Online service), _edistributor. |
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776 | 0 | 8 |
_iPrint version: _z9780471656050 |
856 | 4 | 2 |
_3Abstract with links to resource _uhttp://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=5769527 |
942 | _cEBK | ||
999 |
_c59686 _d59686 |