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Dorr, Bonnie J.

doi:10.1023/a:1007965530302

Cited by 79 publications

References 43 publications

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Inducing terminologies from text: A case study for the consumer health domain

Muresan

Klavans

2013

J Am Soc Inf Sci Tec

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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 webaccessible 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) automatic extraction of definitions from consumer-oriented articles and web documents, which reflects language in use, rather than relying solely on dictionaries, and 2) learning 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.

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