6 citations · 25 across the 12 of their papers we have counts for
4 papers · 1 filter
Entity Type Prediction Leveraging Graph Walks and Entity Descriptions
Russa Biswas, Jan Portisch, Heiko Paulheim +2
The entity type information in Knowledge Graphs (KGs) such as DBpedia, Freebase, etc. is often incomplete due to automated generation or human curation. Entity typing is the task o…
KERMIT -- A Transformer-Based Approach for Knowledge Graph Matching
Sven Hertling, Jan Portisch, Heiko Paulheim
One of the strongest signals for automated matching of knowledge graphs and ontologies are textual concept descriptions. With the rise of transformer-based language models, text co…
Matching with Transformers in MELT
Sven Hertling, Jan Portisch, Heiko Paulheim
One of the strongest signals for automated matching of ontologies and knowledge graphs are the textual descriptions of the concepts. The methods that are typically applied (such as…
KGvec2go -- Knowledge Graph Embeddings as a Service
Jan Portisch, Michael Hladik, Heiko Paulheim
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 emb…