@@ -9,7 +9,8 @@ patterns. Given a source, the learned patterns will try to lead you to the right
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target.
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The algorithm was first developed on a list of human associations that had been
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- mapped to DBpedia entities, as can be seen in [ data/gt_associations.csv] :
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+ mapped to DBpedia entities, as can be seen in
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+ [ data/gt_associations.csv] ( ./data/gt_associations.csv ) :
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| source | target |
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| --------------------------------- | --------------------------------- |
@@ -27,15 +28,15 @@ your list of source-target-pairs is less complicated, the algorithm will happily
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terminate earlier.
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You can find more information about the algorithm and learning patterns for
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- human associations on [ https://w3id.org/associations ] . The page also includes
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+ human associations on https://w3id.org/associations . The page also includes
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publications, as well as the resulting patterns learned for human associations
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from a local DBpedia endpoint including wikilinks.
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Installation
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------------
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- Currently the suggested installation method is via git clone (also allows easier
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+ For now, the suggested installation method is via git clone (also allows easier
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contributions):
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git clone [email protected] :RDFLib/graph-pattern-learner.git
@@ -106,3 +107,9 @@ patterns generalise, you can run:
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The script will then first learn patterns, visualise them in
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` ./results/bundle_name/visualise ` , before evaluating predictions on first the
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training- and then the test-set.
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+
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+
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+ Contributors
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+ ------------
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+ * Jörn Hees
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+ * Rouven Bauer (visualise code)
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