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Evaluation of semantic-based information retrieval methods in the autism phenotype domain
2011
AMIA Annual Symposium Proceedings
Biomedical ontologies are increasingly being used to improve information retrieval methods. In this paper, we present a novel information retrieval approach that exploits knowledge specified by the Semantic Web ontology and rule languages OWL and SWRL. We evaluate our approach using an autism ontology that has 156 SWRL rules defining 145 autism phenotypes. Our approach uses a vector space model to correlate how well these phenotypes relate to the publications used to define them. We compare a
pmid:22195112
pmcid:PMC3243127
fatcat:ze44p4f4znhdbkrbmijol4n3ym