id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_mcnxmtrdrrgu5kghkduzzfdf54	Hadi Fanaee-T	Eigenspace method for spatiotemporal hotspot detection	2014	11	.pdf	application/pdf	8744	709	64	Abstract: Hotspot detection aims at identifying sub-groups in the observations that are unexpected, with respect to some baseline information. For instance, in disease surveillance, the purpose is to detect sub-regions in spatiotemporal space, where the count of reported diseases (e.g. cancer) elements in the principal spatial and the temporal singular vectors, the location of hotspots in the spatiotemporal space can be approximated. The experimental evaluation, both on simulated and real data sets, reveals the effectiveness of the proposed method. of the reported diseases in a range of postal codes, throughout different years as the cases data set. clustering method for hotspot detection, which is widely Spatial scan statistics (Kulldorff, 1997) requires computation time of O(N3) cost practically has restricted their use in real-time applications or large-scale data sets. and time related to tc1 from both baseline and cases data sets, We then apply STScan and EigenSpot on all data sets	./cache/work_mcnxmtrdrrgu5kghkduzzfdf54.pdf	./txt/work_mcnxmtrdrrgu5kghkduzzfdf54.txt