Michael Hladik


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KGvec2go – Knowledge Graph Embeddings as a Service
Jan Portisch | Michael Hladik | Heiko Paulheim
Proceedings of the 12th Language Resources and Evaluation Conference

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.