NLM’s Unified Medical Language System (UMLS) is a very large ontology of biomedical and health data. In order to be used effectively for knowledge processing, it needs to be customized to a specific domain. In this paper, we present techniques to automatically discover domain-specific concepts, discover relationships between these concepts, build a context map from these relationships, link these domain concepts with the best-matching concept identifiers in UMLS using our context map and UMLS concept trees, and finally assign categories to the discovered relationships. This specific domain ontology of terms and relationships using evidential information can serve as a basis for applications in analysis, reasoning and discovery of new relationships. We have automatically built an ontology for the Nuclear Cardiology domain as a testbed for our techniques.
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Domain Ontology Construction from Biomedical Text
by Saurav Sahay, Baoli Li, Ernie Garcia, Eugene Agichtein, Ashwin Ram
International Conference on Artificial Intelligence (ICAI-07), Las Vegas, NV, June 2007www.cc.gatech.edu/faculty/ashwin/papers/er-07-10.pdf