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Analyzing Time Interval Data
Analyzing Time Interval Data
Knygos.lt klubas Knygos.lt nariams
83,64 €
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119,49 €
  • Išsiųsime per 12–18 d.d.
Philipp Meisen introduces a model, a query language, and a similarity measure enabling users to analyze time interval data. The introduced tools are combined to design and realize an information system. The presented system is capable of performing analytical tasks (avoiding any type of summarizability problems), providing insights, and visualizing results processing millions of intervals within milliseconds using an intuitive SQL-based query language. The heart of the solution is based on seve…
  • Leidėjas:
  • Metai: 2016
  • Puslapiai: 232
  • ISBN-10: 3658157275
  • ISBN-13: 9783658157272
  • Formatas: 14.8 x 21 x 2.2 cm, kieti viršeliai
  • Kalba: Anglų

Analyzing Time Interval Data (el. knyga) (skaityta knyga) | knygos.lt

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Philipp Meisen introduces a model, a query language, and a similarity measure enabling users to analyze time interval data. The introduced tools are combined to design and realize an information system. The presented system is capable of performing analytical tasks (avoiding any type of summarizability problems), providing insights, and visualizing results processing millions of intervals within milliseconds using an intuitive SQL-based query language. The heart of the solution is based on several bitmap-based indexes, which enable the system to handle huge amounts of time interval data.

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  • Autorius: Philipp Meisen
  • Leidėjas:
  • Metai: 2016
  • Puslapiai: 232
  • ISBN-10: 3658157275
  • ISBN-13: 9783658157272
  • Formatas: 14.8 x 21 x 2.2 cm, kieti viršeliai
  • Kalba: Anglų

Philipp Meisen introduces a model, a query language, and a similarity measure enabling users to analyze time interval data. The introduced tools are combined to design and realize an information system. The presented system is capable of performing analytical tasks (avoiding any type of summarizability problems), providing insights, and visualizing results processing millions of intervals within milliseconds using an intuitive SQL-based query language. The heart of the solution is based on several bitmap-based indexes, which enable the system to handle huge amounts of time interval data.

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