Isbn: 9783642001925 - Soft Computing for Data Mining Applications: 190 (studies in Computational Intelligence, 190) (10 results)

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  • Language: English

    Published by Springer, 2009

    3642001920 / 9783642001925

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  • Language: English

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  • Language: English

    Published by Springer, 2009

    3642001920 / 9783642001925

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    Condition: New. pp. 364.

  • Language: English

    Published by Springer-Verlag GmbH, 2009

    3642001920 / 9783642001925

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    Condition: Sehr gut. Zustand: Sehr gut | Seiten: 342 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

  • Language: English

    Published by Springer, Berlin, Springer, 2009

    3642001920 / 9783642001925

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    Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The authors have consolidated their research work in this volume titled Soft Computing for Data Mining Applications. The monograph gives an insight into the research in the elds of Data Mining in combination with Soft Computing methodologies. In these days, the data continues to grow - ponentially. Much of the data is implicitly or explicitly imprecise. Database discovery seeks to discover noteworthy, unrecognized associations between the data items in the existing database. The potential of discovery comes from the realization that alternate contexts may reveal additional valuable information. The rate at which the data is storedis growing at a phenomenal rate. Asaresult,traditionaladhocmixturesofstatisticaltechniquesanddata managementtools are no longer adequate for analyzing this vast collection of data. Severaldomainswherelargevolumesofdataarestoredincentralizedor distributeddatabasesincludesapplicationslikeinelectroniccommerce,bio- formatics, computer security, Web intelligence, intelligent learning database systems, nance,marketing,healthcare,telecommunications,andother elds. E cient tools and algorithms for knowledge discovery in large data sets have been devised during the recent years. These methods exploit the ca- bility of computers to search huge amounts of data in a fast and e ective manner. However,the data to be analyzed is imprecise and a icted with - certainty. In the case of heterogeneous data sources such as text and video, the data might moreover be ambiguous and partly con icting. Besides, p- terns and relationships of interest are usually approximate. Thus, in order to make the information mining process more robust it requires tolerance toward imprecision, uncertainty and exceptions.

  • Language: English

    Published by Springer, 2009

    3642001920 / 9783642001925

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  • Language: English

    Published by Berlin Springer Berlin Heidelberg Springer Mrz 2009, 2009

    3642001920 / 9783642001925

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    Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The authors have consolidated their research work in this volume titled Soft Computing for Data Mining Applications. The monograph gives an insight into the research in the elds of Data Mining in combination with Soft Computing methodologies. In these days, the data continues to grow - ponentially. Much of the data is implicitly or explicitly imprecise. Database discovery seeks to discover noteworthy, unrecognized associations between the data items in the existing database. The potential of discovery comes from the realization that alternate contexts may reveal additional valuable information. The rate at which the data is storedis growing at a phenomenal rate. Asaresult,traditionaladhocmixturesofstatisticaltechniquesanddata managementtools are no longer adequate for analyzing this vast collection of data. Severaldomainswherelargevolumesofdataarestoredincentralizedor distributeddatabasesincludesapplicationslikeinelectroniccommerce,bio- formatics, computer security, Web intelligence, intelligent learning database systems, nance,marketing,healthcare,telecommunications,andother elds. E cient tools and algorithms for knowledge discovery in large data sets have been devised during the recent years. These methods exploit the ca- bility of computers to search huge amounts of data in a fast and e ective manner. However,the data to be analyzed is imprecise and a icted with - certainty. In the case of heterogeneous data sources such as text and video, the data might moreover be ambiguous and partly con icting. Besides, p- terns and relationships of interest are usually approximate. Thus, in order to make the information mining process more robust it requires tolerance toward imprecision, uncertainty and exceptions. 341 pp. Englisch.

  • Language: English

    Published by Springer Berlin Heidelberg, 2009

    3642001920 / 9783642001925

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recent research in the fields of Data Mining in combination with Soft Computing methodologiesState-of-the-art technology in data miningThe authors have consolidated their research work in this volume titled Soft Computing for Data Mining A.

  • Language: English

    Published by Springer, 2009

    3642001920 / 9783642001925

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    Condition: New. Print on Demand pp. 364 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.

  • Language: English

    Published by Springer, 2009

    3642001920 / 9783642001925

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    Condition: New. PRINT ON DEMAND pp. 364.