KGvec2go – Knowledge Graph Embeddings as a Service

Jan Portisch, Michael Hladik, Heiko Paulheim


Abstract
In this paper, we present KGvec2go, a Web API for accessing and consuming graph embeddings in a light-weight fashion in downstream applications. Currently, we serve pre-trained embeddings for four knowledge graphs. We introduce the service and its usage, and we show further that the trained models have semantic value by evaluating them on multiple semantic benchmarks. The evaluation also reveals that the combination of multiple models can lead to a better outcome than the best individual model.
Anthology ID:
2020.lrec-1.692
Volume:
Proceedings of the 12th Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
5641–5647
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.692
DOI:
Bibkey:
Cite (ACL):
Jan Portisch, Michael Hladik, and Heiko Paulheim. 2020. KGvec2go – Knowledge Graph Embeddings as a Service. In Proceedings of the 12th Language Resources and Evaluation Conference, pages 5641–5647, Marseille, France. European Language Resources Association.
Cite (Informal):
KGvec2go – Knowledge Graph Embeddings as a Service (Portisch et al., LREC 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.lrec-1.692.pdf