Augmenting spatio-textual search with an infectious disease ontology

Author

Lieberman, Michael D. ; Sankaranarayanan, Jagan ; Samet, Hanan ; Sperling, Jon

Author_Institution

Dept. of Comput. Sci., Univ. of Maryland, College Park, MD

fYear

2008

fDate

7-12 April 2008

Firstpage

266

Lastpage

269

Abstract

A system is described that automatically categorizes and classifies infectious disease incidence reports by type and geographic location, to aid analysis by domain experts. It identifies references to infectious diseases by using a disease ontology. The system leverages the textual and spatial search capabilities of the STEWARD system to enable queries such as reports on "influenza" near "Hong Kong", possibly within a particular time period. Documents from the U.S. National Library of Medicine (http://www.pubmed.gov) and the World Health Organization (http://www.who.int) are tagged so that spatial relationships to specific disease occurrences can be presented graphically via a map interface. In addition, newspaper articles can be tagged and indexed to bolster the surveillance of ongoing epidemics. Examining past epidemics using this system may lead to improved understanding of the cause and spread of infectious diseases.

Keywords

classification; diseases; indexing; medical information systems; ontologies (artificial intelligence); search engines; STEWARD system; classification; epidemics; indexing; infectious disease; map interface; newspaper article; ontology; spatio-textual search; Automation; Computer science; Diseases; Educational institutions; Humans; Influenza; Libraries; Monitoring; Ontologies; Surveillance;

fLanguage

English

Publisher

ieee

Conference_Titel

Data Engineering Workshop, 2008. ICDEW 2008. IEEE 24th International Conference on

Conference_Location

Cancun

Print_ISBN

978-1-4244-2161-9

Electronic_ISBN

978-1-4244-2162-6

Type

conf

DOI

10.1109/ICDEW.2008.4498330

Filename

4498330