Approximating query is one of the operations for resource management in graph database.Existing works mainly based on the distance similarity to measure the query and graphs without considering the semantic similarity.For the approximating query on semantic graphs

disregarding the semantic similarity may fail the query.In this paper

we propose a semantic-based measure for approximating query on RDF graphs

considering the semantic similarity.In the meanwhile

we specify a semantic structural pruning strategy to ameliorate the efficiency of query process.Finally

we construct the query framework to answer approximating query

and design experiments to test our methods under this framework.Results show that the approaches in this paper can efficiently e

xecute approximating query on RDF graphs and effectively return top-

k

results.