English

KGvec2go -- Knowledge Graph Embeddings as a Service

Computation and Language 2020-03-13 v1 Artificial Intelligence Databases

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.

Keywords

Cite

@article{arxiv.2003.05809,
  title  = {KGvec2go -- Knowledge Graph Embeddings as a Service},
  author = {Jan Portisch and Michael Hladik and Heiko Paulheim},
  journal= {arXiv preprint arXiv:2003.05809},
  year   = {2020}
}

Comments

to be published in the Proceedings of the International Conference on Language Resources and Evaluation (LREC) 2020

R2 v1 2026-06-23T14:12:52.265Z