Deep Learning for Spatio-Temporal Data Mining: A Survey

With the fast development of various positioning techniques such as Global Position System (GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly available nowadays. Mining valuable knowledge from spatio-temporal data is critically important to many real-world applica...

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Veröffentlicht in:	IEEE transactions on knowledge and data engineering Jg. 34; H. 8; S. 1
Hauptverfasser:	Wang, Senzhang, Cao, Jiannong, Yu, Philip
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.08.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Analytical models Anomalies Artificial neural networks Crime Data mining Data models Deep learning Demand analysis Domains Electronic devices Environmental management Location based services Machine learning Meteorology Neural networks Public safety Recurrent neural networks Remote sensing Social networks Spatio-temporal data Spatiotemporal data Statistical methods Task analysis Trajectory Transportation Urban planning
ISSN:	1041-4347, 1558-2191
Online-Zugang:	Volltext
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