KGloVe DBpedia predicate object frequency embeddings

Item Type:	Dataset
Title:	KGloVe DBpedia predicate object frequency embeddings
Date:	2017
Creator:	Cochez, Michael ; Ristoski, Petar ORCID: 0000-0002-1890-1507 ; Ponzetto, Simone Paolo ORCID: 0000-0001-7484-2049 ; Paulheim, Heiko ORCID: 0000-0003-4386-8195
Divisions:	School of Business Informatics and Mathematics > Information Systems III: Enterprise Data Analysis (Ponzetto 2016-) School of Business Informatics and Mathematics > Data Science (Paulheim 2018-)

DDC Classification:	004 Computer science, internet
Abstract:	This dataset contains the vectors from computing KGloVe embeddings from a predicate object 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.
External Identifier for Data:	https://doi.org/10.5281/zenodo.1320154

URL:	https://madata.bib.uni-mannheim.de/535/
Access (Controlled):	Only Metadata
License (Controlled):	Creative Commons: CC-BY-SA | Attribution-Share Alike 4.0
Related Publication(s) in MADOC:	Cochez, Michael und Ristoski, Petar und Ponzetto, Simone Paolo und Paulheim, Heiko (2017), Global RDF vector space embeddings

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Date Deposited:	13 Mar 2026 13:51
Last Modified:	13 Mar 2026 13:51