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README.rst

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@@ -143,6 +143,13 @@ embeddings and get literals from a given Knowledge Graph (KG) and entities:
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# Mediterranean', 'Member states of the United Nations'), 0.939]
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# ]
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If you are using a dataset other than MUTAG (where the interested entities have
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no parents in the KG), it is **highly recommended** to specify
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``with_reverse=True`` (defaults to ``False``) in the walking strategy (e.g.,
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``RandomWalker``). Such a parameter **allows Word2Vec** to have a better
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learning window for an entity based on its parents and children and thus
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**predict test data with better accuracy**.
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In a more concrete way, we provide a blog post with a tutorial on how to use
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``pyRDF2Vec`` `here
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<https://towardsdatascience.com/how-to-create-representations-of-entities-in-a-knowledge-graph-using-pyrdf2vec-82e44dad1a0>`__.

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