ISBN: 9783642101250 - soft computing for data mining applications: 190 (studies in computational intelligence) (6 resultados)

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  • Idioma: Inglés

    Editorial: Springer, 2010

    3642101259 / 9783642101250

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Taschenbuch. Condición: 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.…

  • Idioma: Inglés

    Editorial: Springer, 2010

    3642101259 / 9783642101250

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    Librería: Mispah books, Redhill, SURRE, Reino UnidoMispah books

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    EUR 309,29

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    Paperback. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

  • Idioma: Inglés

    Editorial: Springer, 2010

    3642101259 / 9783642101250

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    Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand

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    EUR 126,26

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    Condición: new. Questo è un articolo print on demand.

  • Idioma: Inglés

    Editorial: Springer Berlin Heidelberg, 2010

    3642101259 / 9783642101250

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    Librería: moluna, Greven, Alemaniamoluna

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    Condición: 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.…

  • Idioma: Inglés

    Editorial: Springer, Springer Okt 2010, 2010

    3642101259 / 9783642101250

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    EUR 160,49

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    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 364 pp. Englisch.…

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    Editorial: Springer Berlin Heidelberg Okt 2010, 2010

    3642101259 / 9783642101250

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    EUR 208,64

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    Taschenbuch. Condición: 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. 364 pp. Englisch.…