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Spatio-temporal data streams

Author: Zdravko Galić
Publisher: New York : Springer, 2016.
Series: SpringerBriefs in computer science.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Galić, Zdravko.
Spatio-temporal data streams.
New York : Springer, 2016
(OCoLC)952788215
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Zdravko Galić
ISBN: 9781493965755 1493965751
OCLC Number: 957557921
Description: 1 online resource (xiv, 107 pages) : illustrations.
Contents: Preface; Acknowledgements; Contents; Acronyms; 1 Introduction; 1.1 From Databases to Data Streams; 1.2 Data Stream Management Systems --
An Overview; 1.3 Data Stream Mining and Knowledge Discovery --
An Overview; References; 2 Spatio-Temporal Continuous Queries; 2.1 Foundation of Continuous Query Processing; 2.1.1 Running Example; 2.2 Stream Windows; 2.2.1 Time-Based Window; 2.2.2 Tuple-Based Window; 2.2.3 Predicate-Based Window; 2.3 OCEANUS --
A Prototype of Spatio-Temporal DSMS; 2.3.1 The Type System; 2.4 Operators; 2.4.1 Lifting Operations to Spatio-Temporal Streaming Data Types. 2.5 Implementation2.5.1 User-Defined Aggregate Functions; 2.5.2 SQL-Like Language Embedding: CSQL; References; 3 Spatio-Temporal Data Streams and Big Data Paradigm; 3.1 Background; 3.2 MobyDick --
A Prototype of Distributed Framework #x83;; 3.2.1 Data Model; 3.2.2 Apache Flink; 3.2.3 Spatio-Temporal Queries; 3.3 Related Work; 3.3.1 Distributed Spatial and Spatio-Temporal Batch Systems; 3.3.2 Centralized DSMS-Based Systems; 3.3.3 Distributed DSMS-Based Systems; 3.4 Final Remarks; References; 4 Spatio-Temporal Data Stream Clustering; 4.1 Introduction; 4.1.1 Spatio-Temporal Clustering. 4.2 Data Stream Clustering4.3 Trajectory Stream Clustering; 4.3.1 Incremental Trajectory Clustering Using Micro- and Macro-Clustering; 4.3.2 CTraStream; 4.3.3 Spatial Quincunx Lattices Based Clustering; 4.4 Bibliographic Notes; References; Index.
Series Title: SpringerBriefs in computer science.
Responsibility: Zdravko Galić.

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  Read more...

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