Surge: Continuous detection of bursty regions over a stream of spatial objects

Kaiyu Feng, Tao Guo, Gao Cong, Sourav S. Bhowmick, Shuai Ma

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Citations (Scopus)

Abstract

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 speci?ed 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 ef?ciency and effectiveness by conducting experiments on real-world datasets.

Original languageEnglish
Title of host publicationProceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1296-1299
Number of pages4
ISBN (Electronic)9781538655207
DOIs
Publication statusPublished - 24 Oct 2018
Externally publishedYes
Event34th IEEE International Conference on Data Engineering, ICDE 2018 - Paris, France
Duration: 16 Apr 201819 Apr 2018

Publication series

NameProceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018

Conference

Conference34th IEEE International Conference on Data Engineering, ICDE 2018
Country/TerritoryFrance
CityParis
Period16/04/1819/04/18

Keywords

  • Burst Detection
  • Spatial Data Management
  • Stream

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