Isbn: 9783838310411 - advances in indexing scientific data: helping science reach new frontiers (6 resultados)

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  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2010

    3838310411 / 9783838310411

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    Taschenbuch. Condición: Neu. Advances in Indexing Scientific Data | Helping Science Reach New Frontiers | Rishi Sinha | Taschenbuch | 172 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838310411 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2010

    3838310411 / 9783838310411

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

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

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Mai 2010, 2010

    3838310411 / 9783838310411

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

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    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The ability to extract information from collected data has always driven science. Today's large computers and automated sensing technologies collect terabytes of data in a few weeks. Extracting information from such large amounts of data is like trying to find a needle in a haystack. This book proposes the use of bitmap indexes to efficiently solve this problem. Earlier solutions around bitmap indexes were either too slow or too large to answer large-range scientific queries, and did not provide a way to efficiently consolidate queried data points into meaningful objects. To solve these problems, we introduce multi-resolution, adaptive bitmap indexes in this book and a novel algorithm to consolidate points into objects of interest. Data is binned at multiple granularities, and indexes created for these bins giving a 10x performance gain compared to traditional bitmaps. Making these indexes adaptive reduces the size requirement, giving a 6x performance improvement over a regular bitmap index of the same size. The consolidation algorithm uses special properties of compressed bitmaps and scientific meshes to create objects in time sub linear in number of points retrieved. 172 pp. Englisch.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2010

    3838310411 / 9783838310411

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    Librería: moluna, Greven, Alemaniamoluna

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    EUR 55,21

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    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sinha RishiDr. Sinha did his Ph. D.(2007) from Univ. of Illinois, Urbana inscientific data management. He has worked as a researcher at theLawrence Berkeley Lab and has many publications and patentapplications to his name. He is curr.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Mai 2010, 2010

    3838310411 / 9783838310411

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    EUR 68,00

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    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The ability to extract information from collected data has always driven science. Today's large computers and automated sensing technologies collect terabytes of data in a few weeks. Extracting information from such large amounts of data is like trying to find a needle in a haystack. This book proposes the use of bitmap indexes to efficiently solve this problem. Earlier solutions around bitmap indexes were either too slow or too large to answer large-range scientific queries, and did not provide a way to efficiently consolidate queried data points into meaningful objects. To solve these problems, we introduce multi-resolution, adaptive bitmap indexes in this book and a novel algorithm to consolidate points into objects of interest. Data is binned at multiple granularities, and indexes created for these bins giving a 10x performance gain compared to traditional bitmaps. Making these indexes adaptive reduces the size requirement, giving a 6x performance improvement over a regular bitmap index of the same size. The consolidation algorithm uses special properties of compressed bitmaps and scientific meshes to create objects in time sub linear in number of points retrieved.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 172 pp. Englisch.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2010

    3838310411 / 9783838310411

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

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    Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The ability to extract information from collected data has always driven science. Today's large computers and automated sensing technologies collect terabytes of data in a few weeks. Extracting information from such large amounts of data is like trying to find a needle in a haystack. This book proposes the use of bitmap indexes to efficiently solve this problem. Earlier solutions around bitmap indexes were either too slow or too large to answer large-range scientific queries, and did not provide a way to efficiently consolidate queried data points into meaningful objects. To solve these problems, we introduce multi-resolution, adaptive bitmap indexes in this book and a novel algorithm to consolidate points into objects of interest. Data is binned at multiple granularities, and indexes created for these bins giving a 10x performance gain compared to traditional bitmaps. Making these indexes adaptive reduces the size requirement, giving a 6x performance improvement over a regular bitmap index of the same size. The consolidation algorithm uses special properties of compressed bitmaps and scientific meshes to create objects in time sub linear in number of points retrieved.…