PUMA
Istituto di Informatica e Telematica     
Cresci S., Del Vigna F., Tesconi M., Avvenuti M. Impromptu crisis mapping to prioritize emergency response. In: Computer, vol. 49 (5) pp. 28 - 37. IEEE Computer Society, 2016.
 
 
Abstract
(English)
To visualize post-emergency damage, a crisis-mapping system uses readily available semantic annotators, a machine-learning classifier to analyze relevant tweets, and interactive maps to rank extracted situational information. The system was validated against data from two recent disasters in Italy.
Subject Machine Learning and Data Mining
Data Visualization
Social Media Analysis
Spatial databases and GIS; Data mining


Icona documento 1) Download Document PDF


Icona documento Open access Icona documento Restricted Icona documento Private

 


Per ulteriori informazioni, contattare: Librarian http://puma.isti.cnr.it

Valid HTML 4.0 Transitional