E-Patroller: A Semantic Technology-Based Public Emergency Monitoring System

被引：0
|
作者：
Wang, Yaojun [1 ]
Gao, Yang [2 ]
Yang, Beijing [3 ]
机构：
[1] Peking Univ, Guanghua Sch Management, Beijing, Peoples R China
[2] Beijing Univ, Sch Econ & Management, Beijing, Peoples R China
[3] Peking Univ, Sch Econ, Beijing, Peoples R China
来源：
2017 IEEE 2ND INTERNATIONAL CONFERENCE ON BIG DATA ANALYSIS (ICBDA) | 2017年
关键词：
sematic technology; machine learning; data mining; public emergency;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Monitoring public safety and emergency require equipment that detects the occurrence of emergencies immediately and creates an exact and detailed information about the situation and location of the emergency. Such tools may assist to alleviate desolation under harsh conditions related to natural or human-made disasters by quickly and semi-automatically identifying the type, extent location, intensity, and implications of the catastrophe. The research aimed to build a system, which can identify emergencies and unexpected disasters, based on social media search and semantic technologies.
引用
收藏
页码：255 / 258
页数：4
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