KGvec2go -- Knowledge Graph Embeddings as a Service
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Abstract (arXiv)
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.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Mar 2020.
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Citing papers per year: 2021: 2; 2022: 3; 2023: 0; 2024: 0; 2025: 1.
6 papers.
- 2022Entity Type Prediction Leveraging Graph Walks and Entity Descriptionscited by 6
- 2022Walk this Way! Entity Walks and Property Walks for RDF2veccited by 5
- 2021Background Knowledge in Schema Matching: Strategy vs. Datacited by 3
- 2022The DLCC Node Classification Benchmark for Analyzing Knowledge Graph Embeddingscited by 3
- 2021FinMatcher at FinSim-2: Hypernym Detection in the Financial Services Domain using Knowledge Graphscited by 2
- 2025Bio-KGvec2go: Serving up-to-date Dynamic Biomedical Knowledge Graph Embeddingscited by 0
- 2025Bio-KGvec2go: Serving up-to-date Dynamic Biomedical Knowledge Graph Embeddings9 Sep 2025
- 2022Entity Type Prediction Leveraging Graph Walks and Entity Descriptions28 Jul 2022
- 2022The DLCC Node Classification Benchmark for Analyzing Knowledge Graph Embeddings13 Jul 2022
- 2022Walk this Way! Entity Walks and Property Walks for RDF2vec5 Apr 2022
- 2021Background Knowledge in Schema Matching: Strategy vs. Data29 Jun 2021
- 2021FinMatcher at FinSim-2: Hypernym Detection in the Financial Services Domain using Knowledge Graphs2 Mar 2021