A hybrid natural language approach to manage semantic interoperability for public health analytics

Maxime Lavigne, Arash Shaban-Nejad, Anya Okhmatovskaia, Luke Mondor, David L. Buckeridge

Research output: Contribution to journalConference article

Abstract

This paper discusses the integration of an ontology with a natural language query engine to calculate and interpret epidemiological indicators for population health assessment. In this paper, we discuss the application of this approach to one type of possible query, which retrieves health determinants, causally associated with diabetes mellitus.

Original languageEnglish (US)
Pages (from-to)269-272
Number of pages4
JournalCEUR Workshop Proceedings
Volume1035
StatePublished - Jan 1 2013
Event12th International Semantic Web Conference, ISWC 2013 - Sydney, Australia
Duration: Oct 23 2013 → …

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Public health
Interoperability
Semantics
Health
Query languages
Medical problems
Ontology
Engines

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

Cite this

A hybrid natural language approach to manage semantic interoperability for public health analytics. / Lavigne, Maxime; Shaban-Nejad, Arash; Okhmatovskaia, Anya; Mondor, Luke; Buckeridge, David L.

In: CEUR Workshop Proceedings, Vol. 1035, 01.01.2013, p. 269-272.

Research output: Contribution to journalConference article

Lavigne, Maxime ; Shaban-Nejad, Arash ; Okhmatovskaia, Anya ; Mondor, Luke ; Buckeridge, David L. / A hybrid natural language approach to manage semantic interoperability for public health analytics. In: CEUR Workshop Proceedings. 2013 ; Vol. 1035. pp. 269-272.
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