Analyzing Time Interval Data Introducing an Information System for Time Interval Data Analysis /

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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 summarizabil...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Meisen, Philipp (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Wiesbaden : Springer Fachmedien Wiesbaden : Imprint: Springer Vieweg, 2016.
Edición:1st ed. 2016.
Temas:
Computer networks .
Data structures (Computer science).
Information theory.
Software engineering.
Computer Communication Networks.
Data Structures and Information Theory.
Software Engineering.
Acceso en línea:Texto Completo

MARC

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245 1 0 |a Analyzing Time Interval Data  |h [electronic resource] :  |b Introducing an Information System for Time Interval Data Analysis /  |c by Philipp Meisen. 
250 |a 1st ed. 2016. 
264 1 |a Wiesbaden :  |b Springer Fachmedien Wiesbaden :  |b Imprint: Springer Vieweg,  |c 2016. 
300 |a XXXI, 232 p. 65 illus., 8 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
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505 0 |a Modeling Time Interval Data -- Querying for Time Interval Data -- Similarity of Time Interval Data -- An Information System for Time Interval Data Analysis. 
520 |a 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. Contents Modeling Time Interval Data Querying for Time Interval Data Similarity of Time Interval Data An Information System for Time Interval Data Analysis Target Groups Researchers and students in the field of information management Business analysts and dispatchers in the fields of online analytical processing (OLAP), data warehousing (DW), business intelligence (BI), workforce management, and data science The Author Philipp Meisen holds a doctoral degree from RWTH Aachen, where he was a research group leader at the Chair of Information Management in Mechanical Engineering. 
650 0 |a Computer networks . 
650 0 |a Data structures (Computer science). 
650 0 |a Information theory. 
650 0 |a Software engineering. 
650 1 4 |a Computer Communication Networks. 
650 2 4 |a Data Structures and Information Theory. 
650 2 4 |a Software Engineering. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783658157272 
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856 4 0 |u https://doi.uam.elogim.com/10.1007/978-3-658-15728-9  |z Texto Completo 
912 |a ZDB-2-SCS 
912 |a ZDB-2-SXCS 
950 |a Computer Science (SpringerNature-11645) 
950 |a Computer Science (R0) (SpringerNature-43710) 

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