Spatiotemporal Frequent Pattern Mining from Evolving Region Trajectories (SpringerBriefs in Computer Science)
Language: English
Published by Springer, 2018
Series: Book 278 of 322 - SpringerBriefs in Computer Science
- Softcover
- New
Seller: Biblios, frankfurt am main, hessen, GermanyBiblios
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- Title
- Spatiotemporal Frequent Pattern Mining from Evolving Region Trajectories (SpringerBriefs in Computer Science)
- Author
- Aydin, Berkay; Angryk, Rafal. A
- Publisher
- Springer
- Publication year
- 2018
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 3319998722
- ISBN 13
- 9783319998725
- Series
- Book 278 of 322: SpringerBriefs in Computer Science
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.
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