Inducing terminologies from text: A case study for the consumer health domain. Issue 4 (1st March 2013)

• Record Type: Journal Article
• Authors: Muresan, Smaranda; Klavans, Judith L.
• Is Part Of: Journal of the American Society for Information Science and Technology. Volume 64:Issue 4(2013:Apr.)
• Page Start: 727
• Page End: 744
• Publication Date: 2013-03-01
• Subjects: Information science -- Periodicals; Information technology -- Periodicals; Sciences de l'information -- Périodiques; Technologie de l'information -- Périodiques; 020.5
• DOI: 10.1002/asi.22787
• Languages: English
• ISSNs: 1532-2882

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>Specialized medical ontologies and terminologies, such as SNOMED CT and the Unified Medical Language System (UMLS), have been successfully leveraged in medical information systems to provide a standard web‐accessible medium for interoperability, access, and reuse. However, these clinically oriented terminologies and ontologies cannot provide sufficient support when integrated into consumer‐oriented applications, because these applications must "understand" both technical and lay vocabulary. The latter is not part of these specialized terminologies and ontologies. In this article, we propose a two‐step approach for building consumer health terminologies from text: 1) <italic>automatic extraction</italic> of definitions from consumer‐oriented articles and web documents, which reflects language in use, rather than relying solely on dictionaries, and 2) <italic>learning</italic> to map definitions expressed in natural language to terminological knowledge by inducing a syntactic‐semantic grammar rather than using hand‐written patterns or grammars. We present quantitative and qualitative evaluations of our two‐step approach, which show that our framework could be used to induce consumer health terminologies from text.</p> </abstract>