Overview
Describes a unique overarching model which can support a wide variety of spatio-temporal graph data
Covers A* and bi-directional search for determining fastest paths over spatio-temporal graphs
Introduces spatio-temporal graph datasets, such as engine measurement data
Applications from the research covered in this book (navigational algorithms), can be used for Uber service and Google's autonomous cars
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Table of contents (8 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book highlights some of the unique aspects of spatio-temporal graph data from the perspectives of modeling and developing scalable algorithms. The authors discuss in the first part of this book, the semantic aspects of spatio-temporal graph data in two application domains, viz., urban transportation and social networks. Then the authors present representational models and data structures, which can effectively capture these semantics, while ensuring support for computationally scalable algorithms.
In the first part of the book, the authors describe algorithmic development issues in spatio-temporal graph data. These algorithms internally use the semantically rich data structures developed in the earlier part of this book. Finally, the authors introduce some upcoming spatio-temporal graph datasets, such as engine measurement data, and discuss some open research problems in the area.
This book will be useful as a secondary text for advanced-level students entering into relevant fields of computer science, such as transportation and urban planning. It may also be useful for researchers and practitioners in the field of navigational algorithms.
Authors and Affiliations
Bibliographic Information
Book Title: Spatio-Temporal Graph Data Analytics
Authors: Venkata M. V. Gunturi, Shashi Shekhar
DOI: https://doi.org/10.1007/978-3-319-67771-2
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-67770-5Published: 09 January 2018
Softcover ISBN: 978-3-319-88486-8Published: 04 June 2019
eBook ISBN: 978-3-319-67771-2Published: 15 December 2017
Edition Number: 1
Number of Pages: X, 100
Number of Illustrations: 31 b/w illustrations, 30 illustrations in colour
Topics: Database Management, Transportation, Regional/Spatial Science