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Original Articles

A parallel approach for improving Geo-SPARQL query performance

, , , &
Pages 383-402 | Received 24 Oct 2013, Accepted 10 Mar 2014, Published online: 03 Apr 2014

Figures & data

Figure 1. The query procedure using the proposed optimization strategy.
Figure 1. The query procedure using the proposed optimization strategy.
Figure 2. Major components of Geo-SPARQL.
Figure 2. Major components of Geo-SPARQL.
Figure 3. Simplified syntax of Geo-SPARQL.
Figure 3. Simplified syntax of Geo-SPARQL.
Figure 4. Definition of query solution.
Figure 4. Definition of query solution.
Figure 5. The map layers of schools and streets in New Haven, CT.
Figure 5. The map layers of schools and streets in New Haven, CT.
Figure 6. Runtime (milliseconds) of Q1 to find the nearby streets of each school in New Haven.
Figure 6. Runtime (milliseconds) of Q1 to find the nearby streets of each school in New Haven.
Figure 7. The maps of the schools in CT and streets in coastal regions of CT.
Figure 7. The maps of the schools in CT and streets in coastal regions of CT.
Figure 8. Runtime (millisecond) of the query Q1 applied to Connecticut using the optimized query engine. The runtime of Q1 with naïve implementation took over 365,797 ms (not shown).
Figure 8. Runtime (millisecond) of the query Q1 applied to Connecticut using the optimized query engine. The runtime of Q1 with naïve implementation took over 365,797 ms (not shown).

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