  Signature-based pruning is broadly accepted as an effective way to improve
query performance of graph template matching on general labeled graphs. Most
existing techniques which utilize signature-based pruning claim its benefits on
all datasets and queries. However, the effectiveness of signature-based pruning
varies greatly among different RDF datasets and highly related with their
dataset characteristics. We observe that the performance benefits from
signature-based pruning depend not only on the size of the RDF graphs, but also
the underlying graph structure and the complexity of queries. This motivates us
to propose a flexible RDF querying framework, called RDF-h, which selectively
utilizes signature-based pruning by evaluating the characteristics of RDF
datasets and query templates. Scalability and efficiency of RDF-h is
demonstrated in experimental results using both real and synthetic datasets.
  Keywords: RDF, Graph Template Matching, Signature-based Pruning
