The design and implementation of the redland RDF application framework
Proceedings of the 10th international conference on World Wide Web
Indexing and Querying XML Data for Regular Path Expressions
Proceedings of the 27th International Conference on Very Large Data Bases
Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
The SPARQL Query Graph Model for Query Optimization
ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
Hexastore: sextuple indexing for semantic web data management
Proceedings of the VLDB Endowment
Extending SPARQL with regular expression patterns (for querying RDF)
Web Semantics: Science, Services and Agents on the World Wide Web
A Hybrid Method of Indexing Multiple-Inheritance Hierarchies
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Relational processing of RDF queries: a survey
ACM SIGMOD Record
CoMoGIS'06 Proceedings of the 2006 international conference on Advances in Conceptual Modeling: theory and practice
Proceedings of the 22nd international conference on World Wide Web
Evaluation of RDF queries via equivalence
Frontiers of Computer Science: Selected Publications from Chinese Universities
TripleBit: a fast and compact system for large scale RDF data
Proceedings of the VLDB Endowment
Generalized Hybrid Encoding of Polyhierarchical Structures
Fundamenta Informaticae - To Andrzej Skowron on His 70th Birthday
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We propose a path-based scheme for storage and retrieval of RDF data using a relational database. The Semantic Web is much anticipated as the next-generation web where high-level processing of web resources are enabled by underlying metadata described in RDF format. A typical application of RDF is to describe ontologies or dictionaries, but in such applications, the size of RDF data is large. As large-size RDF data are emerging and their number is increasing, RDF databases that can manage large-size RDF data are becoming ever more important. To date, some RDF databases have already been proposed; however, they have critical problems: the performance of path queries is insufficient and they cannot discriminate between schema data and instance data. In this paper, as a solution to these problems, we propose a path-based relation RDF database. In our approach, we first divide the RDF graph into subgraphs, and then store each subgraph by applicable techniques into distinct relational tables. More precisely, all classes and properties are extracted from RDF schema data, and all resources are also extracted from RDF data. Each is assigned an identifier and a path expression, and stored in corresponding relational table. Because our proposed scheme retains schema information and path expressions of each resource, unlike most conventional RDF databases, it is possible to process path-based queries efficiently and store RDF instance data without schema information. The effectiveness of this approach is demonstrated through several experiments.