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Spatio-Temporal Data Streams / by Zdravko Galic

By: Galic, Zdravko
Contributor(s): SpringerLink (Online service)
Material type: materialTypeLabelE-bookSeries: (SpringerBriefs in Computer Science, 2191-5768).Publisher: New York, NY : Springer New York, 2016Description: 1 recurso en línea (XIV, 107 páginas) : 28 ilustraciones.ISBN: 9781493965755.Subject: Sistemas de gestión de bases de datos | Redes informáticasOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Introduction -- Spatio-Temporal Continuous Queries -- Spatio-Temporal Data Streams and Big Data Paradigm -- Spatio-Temporal Data Stream Clustering.
Abstract: This SpringerBrief presents the fundamental concepts of a specialized class of data stream, spatio-temporal data streams, and demonstrates their distributed processing using Big Data frameworks and platforms. It explores a consistent framework which facilitates a thorough understanding of all different facets of the technology, from basic definitions to state-of-the-art techniques. Key topics include spatio-temporal continuous queries, distributed stream processing, SQL-like language embedding, and trajectory stream clustering. Over the course of the book, the reader will become familiar with spatio-temporal data streams management and data flow processing, which enables the analysis of huge volumes of location-aware continuous data streams. Applications range from mobile object tracking and real-time intelligent transportation systems to traffic monitoring and complex event processing. Spatio-Temporal Data Streams is a valuable resource for researchers studying spatio-temporal data streams and Big Data analytics, as well as data engineers and data scientists solving data management and analytics problems associated with this class of data.
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Holdings
Item type Current library Collection Call number Copy number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería QA76.9.D3 G355 2016 EB (Browse shelf(Opens below)) .i11582479 Acceso electrónico eBOOK .i11582479
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Introduction -- Spatio-Temporal Continuous Queries -- Spatio-Temporal Data Streams and Big Data Paradigm -- Spatio-Temporal Data Stream Clustering.

This SpringerBrief presents the fundamental concepts of a specialized class of data stream, spatio-temporal data streams, and demonstrates their distributed processing using Big Data frameworks and platforms. It explores a consistent framework which facilitates a thorough understanding of all different facets of the technology, from basic definitions to state-of-the-art techniques. Key topics include spatio-temporal continuous queries, distributed stream processing, SQL-like language embedding, and trajectory stream clustering. Over the course of the book, the reader will become familiar with spatio-temporal data streams management and data flow processing, which enables the analysis of huge volumes of location-aware continuous data streams. Applications range from mobile object tracking and real-time intelligent transportation systems to traffic monitoring and complex event processing. Spatio-Temporal Data Streams is a valuable resource for researchers studying spatio-temporal data streams and Big Data analytics, as well as data engineers and data scientists solving data management and analytics problems associated with this class of data.

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