RescueMark: Visual Analytics of Social Media Data for Guiding Emergency Response in Disaster Situations: Award for Skillful Integration of Language Model
| Autor: | Astrik Jeitler, Juri Buchmüller, Denis Makarov, Daniel A. Keim, Timo Jockers, Alpin Turkoglu, Udo Schlegel |
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| Rok vydání: | 2019 |
| Předmět: |
Visual analytics
Computer science Event (computing) Process (engineering) 02 engineering and technology Human-centered computing Visualization Visualization application domains Visual analytics Data science Human-centered computing Visualization 03 medical and health sciences 0302 clinical medicine Data Applied 030221 ophthalmology & optometry 0202 electrical engineering electronic engineering information engineering Resource allocation 020201 artificial intelligence & image processing Social media ddc:004 |
| Zdroj: | VAST |
| DOI: | 10.1109/vast47406.2019.8986898 |
| Popis: | This paper presents RescueMark, a web-based visual analytics tool for analyzing disaster situations and guiding emergency response. In disaster situations operators must take quick and effective decisions to solve critical problems. RescueMark provides spatial, topic and temporal event exploration supporting decision making for resource allocation and determine damaged areas of the city. We describe the data analysis and visualization process of the social media data applied to extract the relevant information. published |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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