mlsanityData to 14 Oct 2026

Spatiotemporal Data Mining: A Survey

arXiv 2206.12753 ↗First posted 26 Jun 2022cs.DB cs.CV cs.DCcited by 3

Not on the map. Why?

Abstract (arXiv)

Spatiotemporal data mining aims to discover interesting, useful but non-trivial patterns in big spatial and spatiotemporal data. They are used in various application domains such as public safety, ecology, epidemiology, earth science, etc. This problem is challenging because of the high societal cost of spurious patterns and exorbitant computational cost. Recent surveys of spatiotemporal data mining need update due to rapid growth. In addition, they did not adequately survey parallel techniques for spatiotemporal data mining. This paper provides a more up-to-date survey of spatiotemporal data mining methods. Furthermore, it has a detailed survey of parallel formulations of spatiotemporal data mining.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 6 of its 79 references that are in the map. First posted on arXiv 26 Jun 2022.

Builds on

6 of 79 references.

References · 6

  1. 2018Learning Spectral-Spatial-Temporal Features via a Recurrent Convolutional Neural Network for Change Detection in Multispectral Imagerycited by 53
  2. 2017Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networkscited by 35
  3. 2019Accident Risk Prediction based on Heterogeneous Sparse Data: New Dataset and Insightscited by 24
  4. 2019TITAN: A Spatiotemporal Feature Learning Framework for Traffic Incident Duration Predictioncited by 4
  5. 2022Understanding COVID-19 Effects on Mobility: A Community-Engaged Approachcited by 4
  6. 2018Balanced k-means for Parallel Geometric Partitioningcited by 2

Built on by

Cited by year

Citing papers per year: 2023: 2; 2024: 1.

3 papers.

  1. 2024A Survey of Generative Techniques for Spatial-Temporal Data Miningcited by 14
  2. 2023Spatial-Temporal Data Mining for Ocean Science: Data, Methodologies, and Opportunitiescited by 5
  3. 2023SERT: A Transfomer Based Model for Spatio-Temporal Sensor Data with Missing Values for Environmental Monitoringcited by 0