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Spatio-Temporal Graph Data Analytics
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This book highlights some of the unique aspects of spatio-temporal graph data from the perspectives of modeling and developingscalable algorithms. The authors discuss in the first part of this book, the semantic aspects of spatio-temporalgraph data in two application domains, viz., urban transportation and social networks.Then the authors present representational models and data structures, which can effectivelycapture 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 algorithmsinternally use the semantically rich data structures developed in the earlierpart of this book. Finally, the authors introduce some upcoming spatio-temporal graph datasets, such as engine measurement data, and discusssome open research problems in the area. This book will be useful as a secondary text for advanced-level students entering into relevantfields of computer science, such as transportation and urban planning. It may alsobe useful for researchers and practitioners in the field of navigational algorithms.
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