Hidden Bibliographic Details
| Other authors / contributors: | Angryk, Rafal A., author.
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| ISBN: | 9783319998732
3319998730
9783319998749
3319998749
9783319998725
3319998722
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| Digital file characteristics: | text file PDF
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| Notes: | Includes bibliographical references and index.
Online resource; title from PDF title page (EBSCO, viewed October 18, 2018).
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| Summary: | 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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| Other form: | Print version: Aydin, Berkay. Spatiotemporal frequent pattern mining from evolving region trajectories. Cham, Switzerland : Springer, 2018 3319998722 9783319998725
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| Standard no.: | 10.1007/978-3-319-99873-2
10.1007/978-3-319-99
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