SURGE: Continuous Detection of Bursty Regions Over a Stream of Spatial Objects

被引：6

作者：

Feng, Kaiyu ^{[1
,2
]}

Guo, Tao ^{[2
]}

Cong, Gao ^{[2
]}

Bhowmick, Sourav S. ^{[2
]}

Ma, Shuai ^{[3
]}

机构：

[1] Nanyang Technol Univ, Interdisciplinary Grad Sch, LILY, Singapore, Singapore

[2] Nanyang Technol Univ, Sch Comp Sci & Engn, Singapore, Singapore

[3] Beihang Univ, SKLSDE Lab, Beijing, Peoples R China

来源：

2018 IEEE 34TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE) | 2018年

关键词：

D O I：

10.1109/ICDE.2018.00133

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

With the proliferation of location-based services, the generation of massive geo-tagged data opens up new opportunities to address real-world problems. In this paper, we present a novel continuous bursty region detection ( SURGE) problem that aims to continuously detect a bursty region of a given size in a specified geographical area from a stream of spatial objects. The SURGE problem is useful in addressing several real-world challenges such as disease outbreak detection. We propose an exact solution to address the problem, and show the efficiency and effectiveness by conducting experiments on real-world datasets.

引用

页码：1292 / 1295

页数：4

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