A graph-based approach for biomedical thesaurus expansion

Abstract

The addition of new terms to biomedical thesauri is important for keeping pace with new research. In the context of a thesaurus expansion task, we investigate the property of Laplacian diffusion kernel matrices that depreciate pivotal vertices having many links to surrounding vertices. We confirm that this property can be seen on the Laplacian matrix of a graph that we construct from the GENIA corpus (a subset of MEDLINE abstracts) and simulate thesaurus expansion by employing either the Laplacian diffusion kernel matrix, or the adjacency matrix (i.e., cosine similarity), to determine the correct position for new biomedical terms being added to the MeSH thesaurus. Whilst results do not show the desired precision, our approach is shown to be complementary to calculation of cosine similarity between thesaurus terms and we recognize directions for future work.