KGloVe DBpedia inverse predicate frequency embeddings

This dataset contains the vectors from computing KGloVe embeddings from a inverse predicate frequency weighted DBpedia 2016-04 graph.

For each entity in the graph, the text file in the zip archive contains a line with the entity name and the embedded vector.

The parameter settings for the embedding are as specified in the paper:

Michael Cochez, Petar Ristoski, Simone Paolo Ponzetto, and Heiko Paulheim. 2017. Global RDF Vector Space Embeddings. In The Semantic Web – ISWC 2017: 16th International Semantic Web Conference, Vienna, Austria, October 21–25, 2017, Proceedings, Part I.