Text mining and ontologies in biomedicine: Making sense of raw text

Irena Spasic, Sophia Ananiadou, John McNaught, Anand Kumar

    Research output: Contribution to journalArticlepeer-review


    The volume of biomedical literature is increasing at such a rate that it is becoming difficult to locate, retrieve and manage the reported information without text mining, which aims to automatically distill information, extract facts, discover implicit links and generate hypotheses relevant to user needs. Ontologies, as conceptual models, provide the necessary framework for semantic representation of textual information. The principal link between text and an ontology is terminology, which maps terms to domain-specific concepts. This paper summarises different approaches in which ontologies have been used for text-mining applications in biomedicine. © Henry Stewart Publications.
    Original languageEnglish
    Pages (from-to)239-251
    Number of pages12
    JournalBriefings in Bioinformatics
    Issue number3
    Publication statusPublished - Sept 2005


    • Information extraction
    • Information retrieval
    • Ontology
    • Terminology
    • Text mining


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