Detect Hidden Road Hazards combining Multiple Social Media Data

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

Abstract

It is imperatively important to spot hidden road hazards which cause a high proportion of traffic incidents. Social media data is featured by its innumerable and up-to-date information, and provides a promising approach to road hazard spotting. However, this research area is not well studied yet. In this paper, we present our view of the important research issues, including challenges of mining spatio-temporal dataset, road hazards reasoning and etc.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE International Conference on Big Data, Big Data 2018
EditorsYang Song, Bing Liu, Kisung Lee, Naoki Abe, Calton Pu, Mu Qiao, Nesreen Ahmed, Donald Kossmann, Jeffrey Saltz, Jiliang Tang, Jingrui He, Huan Liu, Xiaohua Hu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4559-4560
Number of pages2
ISBN (Electronic)9781538650356
DOIs
StatePublished - Jan 22 2019
Event2018 IEEE International Conference on Big Data, Big Data 2018 - Seattle, United States
Duration: Dec 10 2018Dec 13 2018

Publication series

NameProceedings - 2018 IEEE International Conference on Big Data, Big Data 2018

Conference

Conference2018 IEEE International Conference on Big Data, Big Data 2018
CountryUnited States
CitySeattle
Period12/10/1812/13/18

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