A probabilistic approach to detect mixed periodic patterns from moving   object data

doi:10.1007/s10707-016-0261-2

CORC > 北京大学 > 地球与空间科学学院

	A probabilistic approach to detect mixed periodic patterns from moving object data
	Li, Jun ; Wang, Jingjing ; Zhang, Junfei ; Qin, Qiming ; Jindal, Tanvi ; Han, Jiawei
刊名	GEOINFORMATICA
	2016
关键词	Moving object data Periodicity detection Periodic behavior Mixed periodic patterns TIME-SERIES DATA NETWORKS
DOI	10.1007/s10707-016-0261-2
英文摘要	The prevalence of moving object data (MOD) brings new opportunities for behavior related research. Periodic behavior is one of the most important behaviors of moving objects. However, the existing methods of detecting periodicities assume a moving object either does not have any periodic behavior at all or just has a single periodic behavior in one place. Thus they are incapable of dealing with many real world situations whereby a moving object may have multiple periodic behaviors mixed together. Aiming at addressing this problem, this paper proposes a probabilistic periodicity detection method called MPDA. MPDA first identifies high dense regions by the kernel density method, then generates revisit time sequences based on the dense regions, and at last adopts a filter-refine paradigm to detect mixed periodicities. At the filter stage, candidate periods are identified by comparing the observed and reference distribution of revisit time intervals using the chi-square test, and at the refine stage, a periodic degree measure is defined to examine the significance of candidate periods to identify accurate periods existing in MOD. Synthetic datasets with various characteristics and two real world tracking datasets validate the effectiveness of MPDA under various scenarios. MPDA has the potential to play an important role in analyzing complicated behaviors of moving objects.; National Natural Science and Civil Aviation research foundation of China [U1533114]; State Key Laboratory of Coal Resources and Safe Mining Open Research Project [SKLCRSM14KFB04]; U.S. National Science Foundation [IIS-0905215, CNS-0931975, CCF-0905014, IIS-1017362]; SCI(E); EI; ARTICLE; qmqin@pku.edu.cn; 4; 715-739; 20
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/450039]
专题	地球与空间科学学院
推荐引用方式 GB/T 7714	Li, Jun,Wang, Jingjing,Zhang, Junfei,et al. A probabilistic approach to detect mixed periodic patterns from moving object data[J]. GEOINFORMATICA,2016.
APA	Li, Jun,Wang, Jingjing,Zhang, Junfei,Qin, Qiming,Jindal, Tanvi,&Han, Jiawei.(2016).A probabilistic approach to detect mixed periodic patterns from moving object data.GEOINFORMATICA.
MLA	Li, Jun,et al."A probabilistic approach to detect mixed periodic patterns from moving object data".GEOINFORMATICA (2016).