AI RESEARCH
Hierarchical Retrieval with Out-Of-Vocabulary Queries: A Case Study on SNOMED CT
arXiv CS.CL
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ArXi:2511.16698v2 Announce Type: replace SNOMED CT is a biomedical ontology with a hierarchical representation, modelling terminological concepts at a large scale. Knowledge retrieval in SNOMED CT is critical for its application but often proves challenging due to linguistic ambiguity, synonymy, polysemy, and so on. This problem is exacerbated when the queries are out-of-vocabulary (OOV), i.e., lacking any equivalent matches in the ontology.