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Designing a Concept-Mining Model for the Extraction of Medical Information in Spanish
Abstract
This article sketches the development of a method for mining concepts applied on medical corpora in Spanish. Such method is based in the approach formulated by Ananiadou and McNaught, who give a special relevance to the need to create and use natural language processing (NLP) tools, in order to extract information from large collections of documents, such as PubMed (www.ncbi.nlm.nih.gov/pubmed/). Thanks to this repository, projects such as the Corpus Genia (www.geniaproject.org), the MEDIE search engine (www.nactem.ac.uk/medie/), which considers syntactic criteria and semantics to extract medical concepts, or the Open Biological and Biomedical Ontology Project (http://obofoundry.org/), which focuses on the development of ontologies that provide an organized knowledge system in biomedicine. Particularly, this proposal focused in two objectives: (1) the extraction of specialized terms and (2) the identification of lexical-semantic relationships, in concrete hyponymy/hypernymy and meronymy.
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