FlowMiner: Finding flow patterns in spatio-temporal databases
Document Type
Conference Proceeding
Publication Date
12-1-2004
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.
Identifier
16244409799 (Scopus)
ISBN
[076952236X]
Publication Title
Proceedings International Conference on Tools with Artificial Intelligence Ictai
External Full Text Location
https://doi.org/10.1109/ICTAI.2004.63
ISSN
10823409
First Page
14
Last Page
21
Recommended Citation
Wang, Junmei; Hsu, Wynne; Lee, Mong Li; and Wang, Jason, "FlowMiner: Finding flow patterns in spatio-temporal databases" (2004). Faculty Publications. 20048.
https://digitalcommons.njit.edu/fac_pubs/20048
