GAZOUILLE: Detecting and Illustrating Local Events from Geolocalized Social Media Streams

被引：2
|
作者：
Houdyer, Pierre [1 ]
Zimmerman, Albrecht [2 ]
Kaytoue, Mehdi [2 ]
Plantevit, Marc [3 ]
Mitchell, Joseph [1 ]
Robardet, Celine [2 ]
机构：
[1] Tapastreet Ltd, Dublin, Ireland
[2] INSA Lyon, CNRS, LIRIS UMR5205, F-69621 Villeurbanne, France
[3] Univ Lyon 1, CNRS, LIRIS UMR5205, F-69622 Lyon, France
来源：
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, PT III | 2015年 / 9286卷
关键词：
D O I：
10.1007/978-3-319-23461-8_29
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We present Gazouille, a system for discovering local events in geo-localized social media streams. The system is based on three core modules: (i) social networks data acquisition on several urban areas, (ii) event detection through time series analysis, and (iii) a Web user interface to present events discovered in real-time in a city, associated to a gallery of social media that characterize the event.
引用
收藏
页码：276 / 280
页数：5
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