Spatiotemporal Frequent Pattern Mining from Evolving Region Trajectories (SpringerBriefs in Computer Science)

Aydin, Berkay; Angryk, Rafal. A

ISBN 10: 3319998722 / ISBN 13: 9783319998725

Editore: Springer, 2018

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Codice articolo 370365523

Dati bibliografici

• Titolo: Spatiotemporal Frequent Pattern Mining from Evolving Region Trajectories (SpringerBriefs in Computer Science)
• Editore: Springer
• Data di pubblicazione: 2018
• Lingua: Inglese
• ISBN 10: 3319998722
• ISBN 13: 9783319998725
• Rilegatura: Brossura
• Condizione: New

Descrizione articolo

Riassunto

This SpringerBrief provides an overview within data mining of spatiotemporal frequent pattern mining from evolving regions to the perspective of relationship modeling among the spatiotemporal objects, frequent pattern mining algorithms, and data access methodologies for mining algorithms. While the focus of this book is to provide readers insight into the mining algorithms from evolving regions, the authors also discuss data management for spatiotemporal trajectories, which has become increasingly important with the increasing volume of trajectories.

This brief describes state-of-the-art knowledge discovery techniques to computer science graduate students who are interested in spatiotemporal data mining, as well as researchers/professionals, who deal with advanced spatiotemporal data analysis in their fields. These fields include GIS-experts, meteorologists, epidemiologists, neurologists, and solar physicists.