Text similarity approach for SNOMED CT primitive concept similarity measure

For the biomedical ontologies, Concept Similarity Measures (CSMs) become important in order to find similar treatments between diseases. For the ontology primitive concepts, they do not have enough definitions because they are partially defined in the ontology so one way to find the similarity between primitive concepts is to apply textual similarity methods between concept names. But existing textual similarity methods cannot give correct similarity degrees for all concept pairs. In this paper, we propose a new primitive concept name similarity measure based on natural language processing to get a better result in concept similarity measure in terms of noun phrase construction analysis. We conduct experiments on the standard clinical ontology SNOMED CT and make the comparison between our proposed method and existing two approaches against human expert results in order to prove our proposed similarity measure give correct and nearest similarity degree between primitive concepts.