Finding association rules in semantic web data

摘要

The amount of ontologies and semantic annotations available on the Web is constantly growing. This new type of complex and heterogeneous graph-structured data raises new challenges for the data mining community. In this paper, we present a novel method for mining association rules from semantic instance data repositories expressed in RDF/(S) and OWL. We take advantage of the schema-level (i.e. Tbox) knowledge encoded in the ontology to derive appropriate transactions which will later feed traditional association rules algorithms. This process is guided by the analyst requirements, expressed in the form of query patterns. Initial experiments performed on semantic data of a biomedical application show the usefulness and efficiency of the approach.