gStore is an open-source native Resource Description Framework （RDF） triple store that answers SPARQL queries by subgraph matching over RDF graphs. However, there are some deficiencies in the original system design,...gStore is an open-source native Resource Description Framework （RDF） triple store that answers SPARQL queries by subgraph matching over RDF graphs. However, there are some deficiencies in the original system design, such as answering simple queries （including one-triple pattern queries）. To improve the efficiency of the system, we reconsider the system design in this paper. Specifically, we propose a new query plan generation module that generates different query plans according to the structures of query graphs. Furthermore, we re-design our vertex encoding strategy to achieve more pruning power and a new multi-join algorithm to speed up the subgraph matching process. Extensive experiments on synthetic and real RDF datasets show that our method outperforms the state-of-the-art algorithms significantly.展开更多
Built specifically for the Semantic Web, triple stores are required to accommodate a large number of RDF triples and remain primarily centralized. As triple stores grow and evolve with time, there is a demanding need ...Built specifically for the Semantic Web, triple stores are required to accommodate a large number of RDF triples and remain primarily centralized. As triple stores grow and evolve with time, there is a demanding need for scalable techniques to remove resource and performance bottlenecks in such systems. To this end, we propose a fully decentralized peer-to-peer architecture for large scale triple stores in which triples are maintained by individual stakeholders, and a semantics-directed search protocol, mediated by topology reorganization, for locating triples of interest. We test our design through simulations and the results show anticipated improvements over existing techniques for distributed triple stores. In addition to engineering future large scale triple stores, our work will in particular benefit the federation of stand-alone triple stores of today to achieve desired scalability.展开更多
文摘gStore is an open-source native Resource Description Framework （RDF） triple store that answers SPARQL queries by subgraph matching over RDF graphs. However, there are some deficiencies in the original system design, such as answering simple queries （including one-triple pattern queries）. To improve the efficiency of the system, we reconsider the system design in this paper. Specifically, we propose a new query plan generation module that generates different query plans according to the structures of query graphs. Furthermore, we re-design our vertex encoding strategy to achieve more pruning power and a new multi-join algorithm to speed up the subgraph matching process. Extensive experiments on synthetic and real RDF datasets show that our method outperforms the state-of-the-art algorithms significantly.
基金primarily conducted while Jing Zhou was affiliated with the School of Electronics and Computer Science,University of Southampton,U.K.supported in part by the Leading Academic Discipline Program,211 Project for Communication University of China (the 3rd phase)
文摘Built specifically for the Semantic Web, triple stores are required to accommodate a large number of RDF triples and remain primarily centralized. As triple stores grow and evolve with time, there is a demanding need for scalable techniques to remove resource and performance bottlenecks in such systems. To this end, we propose a fully decentralized peer-to-peer architecture for large scale triple stores in which triples are maintained by individual stakeholders, and a semantics-directed search protocol, mediated by topology reorganization, for locating triples of interest. We test our design through simulations and the results show anticipated improvements over existing techniques for distributed triple stores. In addition to engineering future large scale triple stores, our work will in particular benefit the federation of stand-alone triple stores of today to achieve desired scalability.
