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Early Works in Spatio-Temporal Mining

Early Works in Spatio-Temporal Mining

Wynne Hsu, Mong Li Lee, Junmei Wang
Copyright: © 2008 |Pages: 18
ISBN13: 9781599043876|ISBN10: 1599043874|ISBN13 Softcover: 9781616926540|EISBN13: 9781599043890
DOI: 10.4018/978-1-59904-387-6.ch006
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MLA

Wynne Hsu , et al. "Early Works in Spatio-Temporal Mining." Temporal and Spatio-Temporal Data Mining, IGI Global, 2008, pp.112-129. https://doi.org/10.4018/978-1-59904-387-6.ch006

APA

W. Hsu , M. Lee, & J. Wang (2008). Early Works in Spatio-Temporal Mining. IGI Global. https://doi.org/10.4018/978-1-59904-387-6.ch006

Chicago

Wynne Hsu , Mong Li Lee, and Junmei Wang. "Early Works in Spatio-Temporal Mining." In Temporal and Spatio-Temporal Data Mining. Hershey, PA: IGI Global, 2008. https://doi.org/10.4018/978-1-59904-387-6.ch006

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Abstract

Spatio-temporal data mining is an emerging area with increasing importance in a variety of applications, such as homeland security, mobile services, surveillance systems, and health monitoring applications. However, mining in spatio-temporal databases is still in its infancy. Existing work on spatio-temporal data mining has mainly focused on three types of patterns: evolution patterns of natural phenomena, frequent movements of objects over time, and space-time clusters. While there has been much research on association rule mining on transactional, spatial, and temporal data, there is little literature on finding interesting associations in spatio-temporal data. In this chapter, we introduce the early attempts at spatio-temporal data mining and review the techniques to discover various interesting spatio-temporal patterns. This is followed by a review of the traditional association rules mining algorithms and their variants on transactional data, temporal data, and spatial data.

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