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Spatiotemporal Frequent Pattern Mining from Evolving Region Trajectories by Berkay Aydin
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Spatiotemporal Frequent Pattern Mining from Evolving Region Trajectories

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Description

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.
Release date Australia
October 18th, 2018
Pages
106
Edition
1st ed. 2018
Audiences
  • Postgraduate, Research & Scholarly
  • Professional & Vocational
Illustrations
32 Illustrations, color; 1 Illustrations, black and white; XIII, 106 p. 33 illus., 32 illus. in color.
ISBN-13
9783319998725
Product ID
28278139

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