Selectivity Estimation of Correlated Properties in RDF Data for SPARQL Query Optimization

Nowadays mainstream RDF Repository Systems are based on RDBMS. The SPARQL query engine translates a SPARQL query into a SQL one, and then the RDBMS executes the SQL query. However the RDBMS optimizers, which usually assume that columns are statistically independent, often underestimate the selectivity of conjunctive predicates and choose a bad query execution plan. It is important for query optimizers to detect correlations among properties. We propose a way of computing property correlations based on ontology itself in order to improve the execution performance of the SQL translated from SPARQL statement queries.