Adapting semantic natural language processing technology to address information overload in influenza epidemic management

Alla Keselman, Graciela Rosemblat, Halil Kilicoglu, Marcelo Fiszman, Honglan Jin, Dongwook Shin, Thomas C. Rindflesch

Research output: Contribution to journalArticlepeer-review


The explosion of disaster health information results in information overload among response professionals. The objective of this project was to determine the feasibility of applying semantic natural language processing (NLP) technology to addressing this overload. The project characterizes concepts and relationships commonly used in disaster health-related documents on influenza pandemics, as the basis for adapting an existing semantic summarizer to the domain. Methods include human review and semantic NLP analysis of a set of relevant documents. This is followed by a pilot test in which two information specialists use the adapted application for a realistic information-seeking task. According to the results, the ontology of influenza epidemics management can be described via a manageable number of semantic relationships that involve concepts from a limited number of semantic types. Test users demonstrate several ways to engage with the application to obtain useful information. This suggests that existing semantic NLP algorithms can be adapted to support information summarization and visualization in influenza epidemics and other disaster health areas. However, additional research is needed in the areas of terminology development (as many relevant relationships and terms are not part of existing standardized vocabularies), NLP, and user interface design.

Original languageEnglish (US)
Pages (from-to)2531-2543
Number of pages13
JournalJournal of the American Society for Information Science and Technology
Issue number12
StatePublished - Dec 2010
Externally publishedYes

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Networks and Communications
  • Artificial Intelligence


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