Social network data analysis for event detection

被引：3
|
作者：
Garcia-Gasulla, Dario [1 ]
Alvarez-Napagao, Sergio [1 ]
Tejeda-Gomez, Arturo [1 ]
Oliva-Felipe, Luis [1 ]
Gomez-Sebastia, Ignasi [1 ]
Bejar, Javier [1 ]
Vazquez-Salceda, Javier [1 ]
机构：
[1] Univ Politecn Cataluna, Barcelona, Spain
来源：
21ST EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE (ECAI 2014) | 2014年 / 263卷
关键词：
D O I：
10.3233/978-1-61499-419-0-1009
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Cities concentrate enough Social Network (SN) activity to empower rich models. We present an approach to event discovery based on the information provided by three SN, minimizing the data properties used to maximize the total amount of usable data. We build a model of the normal city behavior which we use to detect abnormal situations (events). After collecting half a year of data we show examples of the events detected and introduce some applications.
引用
收藏
页码：1009 / 1010
页数：2
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