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2018 | OriginalPaper | Buchkapitel

1. A Gentle Introduction to Spatiotemporal Data Mining

verfasst von : Berkay Aydin, Rafal A. Angryk

Erschienen in: Spatiotemporal Frequent Pattern Mining from Evolving Region Trajectories

Verlag: Springer International Publishing

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Abstract

Spatiotemporal data mining refers to the extraction of knowledge, regularly repeating relationships, and interesting patterns from data with spatial and temporal aspects. In recent years, many spatiotemporal frequent pattern mining algorithms were developed for spatiotemporal event instances represented by a series of region objects that evolves over time. These algorithms focus on the discovery of spatiotemporal co-occurrence patterns and event sequences by inspecting the spatiotemporal overlap and follow relationships. Before moving onto these relationships, we will demonstrate different types of spatiotemporal knowledge to place the relationships and methods in the greater context. This chapter provides a bird-eye view on the output of spatiotemporal data mining techniques in the literature, gives rationale for mining spatiotemporal patterns from evolving regions, and explains the challenges of mining patterns from evolving region data.

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Nächstes Kapitel Modeling Spatiotemporal Trajectories
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Metadaten
Titel
A Gentle Introduction to Spatiotemporal Data Mining
verfasst von
Berkay Aydin
Rafal A. Angryk
Copyright-Jahr
2018
Buch
Spatiotemporal Frequent Pattern Mining from Evolving Region Trajectories

Print ISBN: 978-3-319-99872-5

Electronic ISBN: 978-3-319-99873-2

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-99873-2_1