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Leveraging Multilingual Descriptions for Link Prediction: Initial Experiments


Leveraging Multilingual Descriptions for Link Prediction: Initial Experiments



Published: 2020 November

Buchtitel: Proceedings of Poster and Demo Track International Conference on Semantic Web
Ausgabe: 2721
Seiten: 84-89
Verlag: CEUR

Referierte Veröffentlichung

BibTeX

Kurzfassung
In most Knowledge Graphs (KGs), textual descriptions of entities are provided in multiple natural languages. Additional informa- tion that is not explicitly represented in the structured part of the KG might be available in these textual descriptions. Link prediction models which make use of entity descriptions usually consider only one language. However, descriptions given in multiple languages may provide comple- mentary information which should be taken into consideration for the tasks such as link prediction. In this poster paper, the benefits of mul- tilingual embeddings for incorporating multilingual entity descriptions into the task of link prediction in KGs are investigated.

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Forschungsgruppe

Information Service Engineering


Forschungsgebiet