Ruben Verborgh’s data

Matches in Ruben’s data for { <https://dx.doi.org/10.3233/SW-180319> ?p ?o }

• SW-180319 author me.
• SW-180319 author me.
• SW-180319 author erik_mannens.
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• SW-180319 about dataset_generator.
• SW-180319 about benchmarking.
• SW-180319 about public_transport.
• SW-180319 about Linked_Data.
• SW-180319 about RDF.
• SW-180319 author me.
• SW-180319 author me.
• SW-180319 author erik_mannens.
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• SW-180319 maker erik_mannens.
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• SW-180319 title "Generating Public Transport Data based on Population Distributions for RDF Benchmarking".
• SW-180319 isPartOf semantic_web_journal.
• SW-180319 name "Generating Public Transport Data based on Population Distributions for RDF Benchmarking".
• SW-180319 label "Generating Public Transport Data based on Population Distributions for RDF Benchmarking".
• SW-180319 name "Generating Public Transport Data based on Population Distributions for RDF Benchmarking".
• SW-180319 topic dataset_generator.
• SW-180319 topic benchmarking.
• SW-180319 topic public_transport.
• SW-180319 topic Linked_Data.
• SW-180319 topic RDF.
• SW-180319 subject dataset_generator.
• SW-180319 subject benchmarking.
• SW-180319 subject public_transport.
• SW-180319 subject Linked_Data.
• SW-180319 subject RDF.
• SW-180319 authorList b0_b2014.
• SW-180319 topic dataset_generator.
• SW-180319 topic benchmarking.
• SW-180319 topic public_transport.
• SW-180319 topic Linked_Data.
• SW-180319 topic RDF.
• SW-180319 abstract "When benchmarking RDF data management systems such as public transport route planners, system evaluation needs to happen under various realistic circumstances, which requires a wide range of datasets with different properties. Real-world datasets are almost ideal, as they offer these realistic circumstances, but they are often hard to obtain and inflexible for testing. For these reasons, synthetic dataset generators are typically preferred over real-world datasets due to their intrinsic flexibility. Unfortunately, many synthetic dataset that are generated within benchmarks are insufficiently realistic, raising questions about the generalizability of benchmark results to real-world scenarios. In order to benchmark geospatial and temporal RDF data management systems such as route planners with sufficient external validity and depth, we designed PODIGG, a highly configurable generation algorithm for synthetic public transport datasets with realistic geospatial and temporal characteristics comparable to those of their real-world variants. The algorithm is inspired by real-world public transit network design and scheduling methodologies. This article discusses the design and implementation of PODIGG and validates the properties of its generated datasets. Our findings show that the generator achieves a sufficient level of realism, based on the existing coherence metric and new metrics we introduce specifically for the public transport domain. Thereby, PODIGG provides a flexible foundation for benchmarking RDF data management systems with geospatial and temporal data.".
• SW-180319 datePublished "2019".
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• SW-180319 number "328".
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