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Concurrent with progress in biomedical sciences, an overwhelming of textual knowledge is accumulating in the biomedical literature. PubMed is the most comprehensive database collecting and managing biomedical literature. To help researchers easily understand collections of PubMed abstracts, numerous clustering methods have been proposed to group similar abstracts based on their shared features. However, most of these methods do not explore the semantic relationships among groupings ofdoi:10.1016/j.jbi.2009.07.006 pmid:19635585 fatcat:wkmwrijq2rctvo7bi4tjgrnef4