Abstract
Spatiotemporal association rules mining is to reveal interrelationships within large spatiotemporal databases. One critical limitation of traditional approaches is that they are confined to qualitative attribute measures. Quantitative frequencies are either ignored or discretized. In this paper, we propose a robust data mining method that efficiently reveals frequency-incorporated associations in spatiotemporal databases.
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Lee, I. (2004). Frequency-Incorporated Interdependency Rules Mining in Spatiotemporal Databases. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30132-5_31
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DOI: https://doi.org/10.1007/978-3-540-30132-5_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23318-3
Online ISBN: 978-3-540-30132-5
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