Unsupervised Crisis Information Extraction from Twitter Data

被引:0
|
作者
Interdonato, Roberto [1 ]
Doucet, Antoine [2 ]
Guillaume, Jean-Loup [2 ]
机构
[1] CIRAD, UMR TETIS, F-34000 Montpellier, France
[2] Univ La Rochelle, L3i, F-17000 La Rochelle, France
关键词
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
While microblogging-based Online Social Networks have become an attractive data source in emergency situations, overcoming information overload is still not trivial. We propose a framework which integrates natural language processing and clustering techniques in order to produce a ranking of relevant tweets based on their informativeness. Experiments on four Twitter collections in two languages (English and French) proved the significance of our approach.
引用
收藏
页码:579 / 580
页数:2
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