Mining Generalized Association Rules on Biomedical Literature

The discovery of new and potentially meaningful relationships between concepts in the biomedical literature has attracted the attention of a lot of researchers in text mining. The main motivation is found in the increasing availability of the biomedical literature which makes it difficult for researchers in biomedicine to keep up with research progresses without the help of c knowledge discovery techniques. More than 14 million abstracts of this literature are contained in the Medline collection and are available online. In this paper we present the application of an association rule mining method to abstracts in order to detect associations between concepts as indication of the existence of a biomedical relation. The discovery process fully exploits the MeSH (Medical Subject Headings) taxonomy, that is, a set of hierarchically related biomedical terms which permits to express associations at different f abstraction (generalized association rules). We report experimental on a collectio...

• Type: Conference
• Year: 2005
• Where: IEAAIE
• Authors: Margherita Berardi, Michele Lapi, Pietro Leo, Corrado Loglisci
• Keywords: Association Rules, Biomedical Literature, IEAAIE 2005, Knowledge Discovery Techniques