Mining periodic spatio-temporal co-occurrence patterns: A summary of results
Küçük Resim Yok
Tarih
2012
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Periodic spatio-temporal co-occurrence patterns (PECOPs) represent subsets of object-types that are often periodically located together in space and time. Discovering PECOPs is an important problem with many applications such as discovering interactions between animals and identifying tactics in games. However, mining PECOPs is computationally very expensive because the interest measures are computationally complex, databases are larger due to the archival history, and the set of candidate patterns is exponential in the number of object-types. In this paper, we define the problem of mining PECOPs, and propose a novel PECOP mining algorithm. The experimental results show that the proposed algorithm is computationally more efficient than the naïve alternatives. © 2012 IEEE.
Açıklama
International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2012 -- 2 July 2012 through 4 July 2012 -- Trabzon -- 92831
Anahtar Kelimeler
dynamic time warping, spatial co-location, spatio-temporal periodic co-occurrence pattern mining spatio-temporal data mining
Kaynak
INISTA 2012 - International Symposium on INnovations in Intelligent SysTems and Applications
WoS Q Değeri
Scopus Q Değeri
N/A
