RescueMark : Visual Analytics of Social Media Data for Guiding Emergency Response in Disaster Situations Award for Skillful Integration of Language Model

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2019
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CHANG, Remco, ed., Daniel A. KEIM, ed., Ross MACIEJEWSKI, ed.. 2019 IEEE Conference on Visual Analytics Science and Technology (VAST) : Proceedings. Piscataway, NJ: IEEE, 2019, pp. 120-121. ISBN 978-1-72812-284-7. Available under: doi: 10.1109/VAST47406.2019.8986898
Zusammenfassung

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.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
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Human-centered computing, Visualization, Visualization application domains, Visual analytics
Konferenz
2019 IEEE Conference on Visual Analytics Science and Technology (VAST), 20. Okt. 2019 - 25. Okt. 2019, Vancouver, BC, Canada
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Zitieren
ISO 690JEITLER, Astrik Veronika, Alpin TÜRKOGLU, Denis MAKAROV, Timo JOCKERS, Juri F. BUCHMÜLLER, Udo SCHLEGEL, Daniel A. KEIM, 2019. RescueMark : Visual Analytics of Social Media Data for Guiding Emergency Response in Disaster Situations Award for Skillful Integration of Language Model. 2019 IEEE Conference on Visual Analytics Science and Technology (VAST). Vancouver, BC, Canada, 20. Okt. 2019 - 25. Okt. 2019. In: CHANG, Remco, ed., Daniel A. KEIM, ed., Ross MACIEJEWSKI, ed.. 2019 IEEE Conference on Visual Analytics Science and Technology (VAST) : Proceedings. Piscataway, NJ: IEEE, 2019, pp. 120-121. ISBN 978-1-72812-284-7. Available under: doi: 10.1109/VAST47406.2019.8986898
BibTex
@inproceedings{Jeitler2019Rescu-50585,
  year={2019},
  doi={10.1109/VAST47406.2019.8986898},
  title={RescueMark : Visual Analytics of Social Media Data for Guiding Emergency Response in Disaster Situations Award for Skillful Integration of Language Model},
  isbn={978-1-72812-284-7},
  publisher={IEEE},
  address={Piscataway, NJ},
  booktitle={2019 IEEE Conference on Visual Analytics Science and Technology (VAST) : Proceedings},
  pages={120--121},
  editor={Chang, Remco and Keim, Daniel A. and Maciejewski, Ross},
  author={Jeitler, Astrik Veronika and Türkoglu, Alpin and Makarov, Denis and Jockers, Timo and Buchmüller, Juri F. and Schlegel, Udo and Keim, Daniel A.}
}
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