Published on 01 January 2013

Graph Sampling for Linked Data

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Rietveld, Laurens;Schlobach, Stefan;Guéret, Christophe;Hoekstra, Rinke;Loizou, Antonis

Description

Results for Graph Sampling for Linked Data, a submission for ISWC 2013 We apply different rewrite methods to transform our RDF graph into an unweighted directed graph with unlabelled edges. The rewritten graph is analysed using different standard network algorithms, after which the weights are aggregated back to the RDF triples. We measure the quality of the subgraph using query logs, where we calculate the recall by executing each query on the subgraph as well as the original graph. Navigatable results (i.e. html) are available here:
http://data2semantics.github.io/GraphSampling/

Citations (0)

Mentions (0)

Metrics

Dataset Index

0.3

FAIR Score

13%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

figshare

Assigned Domain

Subfield

Artificial Intelligence

Field

Computer Science

Domain

Physical Sciences

Confidence Score

100%

Source

Open Alex

Keywords

Applied Computer Science

Normalization Factors

FT

13.46

CTw

1.00

MTw

1.00