The Resource Spatio-temporal data streams, Zdravko Galić

Spatio-temporal data streams, Zdravko Galić

Label
Spatio-temporal data streams
Title
Spatio-temporal data streams
Statement of responsibility
Zdravko Galić
Creator
Author
Subject
Genre
Language
eng
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 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
Member of
Cataloging source
N$T
http://library.link/vocab/creatorName
Galić, Zdravko
Dewey number
006.7/876
Illustrations
illustrations
Index
index present
LC call number
TK5105.386
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Series statement
SpringerBriefs in computer science,
http://library.link/vocab/subjectName
  • Streaming technology (Telecommunications)
  • Data mining
  • COMPUTERS
  • Data mining
  • Computer Science
  • Database Management
  • Geographical Information Systems/Cartography
  • Computer Communication Networks
  • Graph Theory
  • Geographical information systems (GIS) & remote sensing
  • Network hardware
  • Combinatorics & graph theory
  • Databases
Label
Spatio-temporal data streams, Zdravko Galić
Link
https://ezproxy.lib.ou.edu/login?url=http://link.springer.com/10.1007/978-1-4939-6575-5
Instantiates
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
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
Dimensions
unknown
Extent
1 online resource (xiv, 107 pages)
File format
unknown
Form of item
online
Isbn
9781493965755
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Note
SpringerLink
Other control number
10.1007/978-1-4939-6575-5
Other physical details
illustrations.
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • (OCoLC)957557921
  • (OCoLC)ocn957557921
Label
Spatio-temporal data streams, Zdravko Galić
Link
https://ezproxy.lib.ou.edu/login?url=http://link.springer.com/10.1007/978-1-4939-6575-5
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
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
Dimensions
unknown
Extent
1 online resource (xiv, 107 pages)
File format
unknown
Form of item
online
Isbn
9781493965755
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Note
SpringerLink
Other control number
10.1007/978-1-4939-6575-5
Other physical details
illustrations.
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • (OCoLC)957557921
  • (OCoLC)ocn957557921

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