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Conference papers
The Pattern Next Door: Towards Spatio-sequential Pattern Discovery
Abstract : Health risks management such as epidemics study produces large quantity of spatio-temporal data. The development of new methods able to manage such specific characteristics becomes crucial. To tackle this problem, we define a theoretical framework for extracting spatio-temporal patterns (sequences representing evolution of locations and their neighborhoods over time). Classical frequency support doesn't consider the pattern neighbor neither its evolution over time. We thus propose a new interestingness measure taking into account both spatial and temporal aspects. An algorithm based on pattern-growth approach with efficient successive projections over the database is proposed. Experiments conducted on real datasets highlight the relevance of our method.
Cited literature [13 references]
https://hal-lirmm.ccsd.cnrs.fr/lirmm-00802125
Contributor : Hugo Alatrista-Salas <>
Submitted on : Tuesday, September 29, 2020 - 2:33:19 PM
Last modification on : Monday, November 30, 2020 - 2:36:03 PM
Long-term archiving on: : Wednesday, December 30, 2020 - 6:46:45 PM
Contributor : Hugo Alatrista-Salas <>
Submitted on : Tuesday, September 29, 2020 - 2:33:19 PM
Last modification on : Monday, November 30, 2020 - 2:36:03 PM
Long-term archiving on: : Wednesday, December 30, 2020 - 6:46:45 PM
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PaperPAKDD2012.pdf
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