Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICTAI.2004.63
Title: FlowMiner: Finding flow patterns in spatio-temporal databases
Authors: Wang, J. 
Hsu, W. 
Lee, M.L. 
Wang, J.
Issue Date: 2004
Source: Wang, J.,Hsu, W.,Lee, M.L.,Wang, J. (2004). FlowMiner: Finding flow patterns in spatio-temporal databases. Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI : 14-21. ScholarBank@NUS Repository. https://doi.org/10.1109/ICTAI.2004.63
Abstract: The widespread use of spatio-temporal databases and applications have fuelled an urgent need to discover interesting time and space patterns in such databases. While much work has been done in discovering time/sequence patterns or spatial patterns, discovering of patterns involving both time and space dimensions is still in its infancy. In this paper, we introduce the concept of flow patterns. Flow patterns are intended to describe the change of events over space and time. These flow patterns are useful to the understanding of many real-life applications. We present a disk-based algorithm, FlowMiner, which utilizes temporal relationships and spatial relationships amid events to generate flow patterns. Our performance study shows that FlowMiner is both scalable and efficient. Experiments on real-life datasets also reveal interesting flow patterns. © 2004 IEEE.
Source Title: Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI
URI: http://scholarbank.nus.edu.sg/handle/10635/40940
ISBN: 076952236X
ISSN: 10823409
DOI: 10.1109/ICTAI.2004.63
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