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Erschienen in:
An Introduction to Frequent Pattern Mining Kapitel lesen Erstes Kapitel lesen

2014 | OriginalPaper | Buchkapitel

12. Spatiotemporal Pattern Mining: Algorithms and Applications

verfasst von : Zhenhui Li

Erschienen in: Frequent Pattern Mining

Verlag: Springer International Publishing

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Abstract

With the fast development of positioning technology, spatiotemporal data has become widely available nowadays. Mining patterns from spatiotemporal data has many important applications in human mobility understanding, smart transportation, urban planning and ecological studies. In this chapter, we provide an overview of spatiotemporal data mining methods. We classify the patterns into three categories: (1) individual periodic pattern; (2) pairwise movement pattern and (3) aggregative patterns over multiple trajectories. This chapter states the challenges of pattern discovery, reviews the state-of-the-art methods and also discusses the limitations of existing methods.

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Vorheriges Kapitel Sequential Pattern Mining
Nächstes Kapitel Mining Graph Patterns
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Metadaten
Titel
Spatiotemporal Pattern Mining: Algorithms and Applications
verfasst von
Zhenhui Li
Copyright-Jahr
2014
Buch
Frequent Pattern Mining

Print ISBN: 978-3-319-07820-5

Electronic ISBN: 978-3-319-07821-2

Copyright-Jahr: 2014

DOI
https://doi.org/10.1007/978-3-319-07821-2_12

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