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 Twelfth Language Resources and Evaluation Conference
- Month:
- May
- Year:
- 2020
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- 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 Twelfth 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
Export citation
@inproceedings{portisch-etal-2020-kgvec2go,
title = "{KG}vec2go {--} Knowledge Graph Embeddings as a Service",
author = "Portisch, Jan and
Hladik, Michael and
Paulheim, Heiko",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.692",
pages = "5641--5647",
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.",
language = "English",
ISBN = "979-10-95546-34-4",
}
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<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.</abstract>
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%0 Conference Proceedings %T KGvec2go – Knowledge Graph Embeddings as a Service %A Portisch, Jan %A Hladik, Michael %A Paulheim, Heiko %Y Calzolari, Nicoletta %Y Béchet, Frédéric %Y Blache, Philippe %Y Choukri, Khalid %Y Cieri, Christopher %Y Declerck, Thierry %Y Goggi, Sara %Y Isahara, Hitoshi %Y Maegaard, Bente %Y Mariani, Joseph %Y Mazo, Hélène %Y Moreno, Asuncion %Y Odijk, Jan %Y Piperidis, Stelios %S Proceedings of the Twelfth Language Resources and Evaluation Conference %D 2020 %8 May %I European Language Resources Association %C Marseille, France %@ 979-10-95546-34-4 %G English %F portisch-etal-2020-kgvec2go %X 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. %U https://aclanthology.org/2020.lrec-1.692 %P 5641-5647
Markdown (Informal)
[KGvec2go – Knowledge Graph Embeddings as a Service](https://aclanthology.org/2020.lrec-1.692) (Portisch et al., LREC 2020)
- KGvec2go – Knowledge Graph Embeddings as a Service (Portisch et al., LREC 2020)
ACL
- Jan Portisch, Michael Hladik, and Heiko Paulheim. 2020. KGvec2go – Knowledge Graph Embeddings as a Service. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 5641–5647, Marseille, France. European Language Resources Association.