Spatio-Temporal Graph Data Analytics

Gunturi, Venkata M. V.; Shekhar, Shashi

Abstract

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.

Citation

Gunturi, V. M. V., & Shekhar, S. (2018). Spatio-Temporal Graph Data Analytics. Springer. https://doi.org/10.1007/978-3-319-67771-2

• Book Type: Authored Book
• Online Publication Date: Dec 15, 2017
• Publication Date: Jan 9, 2018
• Deposit Date: Sep 27, 2023
• Publisher: Springer
• ISBN: 9783319677705; 9783319884868
• DOI: https://doi.org/10.1007/978-3-319-67771-2
• Public URL: https://hull-repository.worktribe.com/output/4401447