In the Semantic Web, metadata and ontology for representing semantics and conceptual relationships of information resources are essential factors. RDF and RDF Schema are the W3C standard models for describing metadata and ontology. In this paper, we focus on a result of analyzing available query patterns considering both RDF and RDF Schema. And we propose a structure to store and query using path information in graph models of RDF and RDF Schema. The proposed structure supports whole query patterns fairly. We can retrieve entities that are reached from a certain class, property, resource, or literal in RDF and RDF Schema without a loss of performance because of multiple joins with tables. And, through encoding schemes, we determine easily hierarchical relationships between classes or properties.

Efficient query processing in multi-dimensional indexing structures is an important issue for multimedia data applications. In this paper, we propose incremental k-nearest neighbor query (k-NNQ) and range query algorithms for R-tree based structures. The novel aspect of these algorithms is that they make use of the notion of VP filtering, a concept borrowed from the MVP-tree. The filtering notion allows for delaying of computational overhead until absolutely necessary. By so doing, we attain considerable performance benefits while paying insignificant overhead during the construction of the index structure. We implemented our algorithms and carried out experiments to demonstrate the capability and usefulness of our method. Results show that improvements range from 8% to 23% in response time for the experimental environment that we considered.