Spatio-Temporal Data Mining
- 22 August 2018
- journal article
- research article
- Published by Association for Computing Machinery (ACM) in ACM Computing Surveys
- Vol. 51 (4), 1-41
- https://doi.org/10.1145/3161602
Abstract
Large volumes of spatio-temporal data are increasingly collected and studied in diverse domains, including climate science, social sciences, neuroscience, epidemiology, transportation, mobile health, and Earth sciences. Spatio-temporal data differ from relational data for which computational approaches are developed in the data-mining community for multiple decades in that both spatial and temporal attributes are available in addition to the actual measurements/attributes. The presence of these attributes introduces additional challenges that needs to be dealt with. Approaches for mining spatio-temporal data have been studied for over a decade in the data-mining community. In this article, we present a broad survey of this relatively young field of spatio-temporal data mining. We discuss different types of spatio-temporal data and the relevant data-mining questions that arise in the context of analyzing each of these datasets. Based on the nature of the data-mining problem studied, we classify literature on spatio-temporal data mining into six major categories: clustering, predictive learning, change detection, frequent pattern mining, anomaly detection, and relationship mining. We discuss the various forms of spatio-temporal data-mining problems in each of these categories.Keywords
Funding Information
- National Science Foundation (1029711)
- NASA (NNX12AP37G)
This publication has 174 references indexed in Scilit:
- Complex biomarker discovery in neuroimaging data: Finding a needle in a haystackNeuroImage: Clinical, 2013
- Neural correlates of establishing, maintaining, and switching brain statesTrends in Cognitive Sciences, 2012
- Stability of graph communities across time scalesProceedings of the National Academy of Sciences of the United States of America, 2010
- Correspondence of the brain's functional architecture during activation and restProceedings of the National Academy of Sciences of the United States of America, 2009
- Detecting influenza epidemics using search engine query dataNature, 2009
- Resolution limit in community detectionProceedings of the National Academy of Sciences of the United States of America, 2007
- Beyond mind-reading: multi-voxel pattern analysis of fMRI dataTrends in Cognitive Sciences, 2006
- Cross-species analysis of biological networks by Bayesian alignmentProceedings of the National Academy of Sciences of the United States of America, 2006
- Modularity and community structure in networksProceedings of the National Academy of Sciences of the United States of America, 2006
- Network motifs in the transcriptional regulation network of Escherichia coliNature Genetics, 2002