RDF Rank is an algorithm, which identifies the more important or more popular entities in the repository by examining their interconnectedness. The popularity of entities can then be used to order query results in a similar way to the internet search engines, such as how Google orders search results using PageRank http://en.wikipedia.org/wiki/PageRank.
As seen in the example query, RDF Rank weights are made available via a special system predicate. Triple patterns with the predicate http://www.ontotext.com/owlim/RDFRank#hasRDFRank are handled specially by GraphDB, where the object of the statement pattern is bound to a literal containing the RDF Rank of the subject.
To trigger the computation of the RDF Rank values for all resources use the following update:
The full computation of RDF Rank values for all resources can be relatively expensive. When new resources have been added to the repository after a previous full computation of RDF Rank vales, then either a full re-computation can be done for all resources (see above) or only the RDF Rank values for the new resources can be computed (an incremental update). The following control update:
computes RDF Rank values for those resources, which do not have an associated value, i.e. those that have been added to the repository since the last full RDF Rank computation.
The computed weights can be exported to an external file using an update of this form:
If the export fails then the update throws an exception and an error message will be recorded in the log file.
Lastly, when using RDF Priming, the RDF Rank values can be used as the initial activation values. To set this up, use the following update:
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