FlowMiner: Finding flow patterns in spatio-temporal databases

Junmei Wang, Wynne Hsu, Mong Li Lee, Jason Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

26 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationProceedings - 16th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2004
EditorsT.M. Khoshgoftaar
Pages14-21
Number of pages8
DOIs
StatePublished - Dec 1 2004
EventProceedings - 16th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2004 - Boca Raton, FL, United States
Duration: Nov 15 2004Nov 17 2004

Publication series

NameProceedings - International Conference on Tools with Artificial Intelligence, ICTAI
ISSN (Print)1082-3409

Other

OtherProceedings - 16th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2004
CountryUnited States
CityBoca Raton, FL
Period11/15/0411/17/04

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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