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

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 info rmation, 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. In this article, we summarize different approaches in which ontologies have been used for text mining applications in biomedicine.

• Type: Journal
• Year: 2005
• Where: BIB
• Authors: Irena Spasic, Sophia Ananiadou, John McNaught, Anand Kumar
• Keywords: BIB 2005, Biomedical Literature, Text Mining, Text Mining Applications