Mining periodic patterns in spatio-temporal sequences at different time granularities

被引:7
|
作者
Karli, Sezin [1 ]
Saygin, Yucel [1 ]
机构
[1] Sabanci Univ, Fac Engn & Nat Sci, TR-34956 Istanbul, Turkey
关键词
Data mining; spatio-temporal data; time granularity; periodic pattern;
D O I
10.3233/IDA-2009-0368
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the advancement of technology, it is now easy to collect the location information of mobile users over time. Spatio-temporal data mining techniques were proposed in the literature for the extraction of patterns from spatio-temporal data. However, current techniques can only extract patterns of the finest time granularity, and therefore overlooks potential patterns available at coarser time granularities. In this work, we propose two techniques to allow mining at different time granularities. Experimental results show that the proposed techniques are indeed effective and efficient for mining periodic spatio-temporal patterns at different time granularities.
引用
收藏
页码:301 / 335
页数:35
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