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Dynamic Graph Analytic Framework (DYGRAF) for biosurveillance support

  • CUBRC

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this work, we leverage Dynamic Graph Analytic Framework (DYGRAF), a domain agnostic framework from which data alignment, data association and layered multi-modal network analysis can be performed. By applying DYGRAF to the discipline of biosurveillance, and incorporating disparate yet related data sets stemming from medical, communication, and financial domains, salient information about the origin and propagation of a pandemic can be identified, including the key people and locations involved in the spread of a disease within and across communities. Through the identification and leveraging of this information, DYGRAF enables an analyst to gain a greater understanding of the current situation, allowing the analyst to develop strategies to limit the extent and effects of the pandemic.

Original languageEnglish
Title of host publicationProceedings of the 16th International Conference on Information Fusion, FUSION 2013
Pages857-863
Number of pages7
StatePublished - 2013
Event16th International Conference of Information Fusion, FUSION 2013 - Istanbul, Turkey
Duration: Jul 9 2013Jul 12 2013

Publication series

NameProceedings of the 16th International Conference on Information Fusion, FUSION 2013

Conference

Conference16th International Conference of Information Fusion, FUSION 2013
Country/TerritoryTurkey
CityIstanbul
Period07/9/1307/12/13

Keywords

  • biosurveillance
  • information fusion
  • multi-modal network analysis
  • situation awareness
  • social network analysis

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