RDF2Vec DBpedia uniform embeddings in HDF5 file format

Item Type:	Dataset
Title:	RDF2Vec DBpedia uniform embeddings in HDF5 file format
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 RDF2vec embeddings from a uniformly weighted DBpedia 2016-04 graph. The file has a group called "Vectors" which contains a dataset for each entity in the graph. The dataset name is the entity name and the dataset content is the embedded vector (length 200). The parameter settings for the embedding are as specified in the paper: Michael Cochez, Petar Ristoski, Simone Paolo Ponzetto, and Heiko Paulheim. 2017. Biased graph walks for RDF graph embeddings. In Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics (WIMS '17). ACM, New York, NY, USA, Article 21, 12 pages. DOI: https://doi.org/10.1145/3102254.3102279
External Identifier for Data:	https://doi.org/10.5281/zenodo.2017356

URL:	https://madata.bib.uni-mannheim.de/556/
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), Biased graph walks for RDF graph embeddings

Full text not available from this repository.

Date Deposited:	13 Mar 2026 16:08
Last Modified:	13 Mar 2026 16:08