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Semantic similarity is useful in different areas of Natural Language Processing (NLP), such as word-sense disambiguation and nameentity recognition, as well as in information retrieval. On the other hand, specialised NLP tools are required in the biomedical context due to the huge amount of information currently available in digital publications that can be explored. This paper presents a method for calculating the semantic similarity between pairs of biomedical concepts defined in an ontology derived from the SNOMED-CT vocabulary. A final semantic similarity is obtained by calculating the similarity between the components of the two concept definitions based on their shared and unshared ancestors in the ontology hierarchy. The results are compared with other methods as well as with human expert ranks as baseline.

Using Concept Definitions and Ontology Structure to Measure Semantic Similarity in Biomedicine