4 citations · 19 across the 9 of their papers we have counts for
3 papers · 1 filter
RAILD: Towards Leveraging Relation Features for Inductive Link Prediction In Knowledge Graphs
Genet Asefa Gesese, Harald Sack, Mehwish Alam
Due to the open world assumption, Knowledge Graphs (KGs) are never complete. In order to address this issue, various Link Prediction (LP) methods are proposed so far. Some of these…
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…
A Knowledge Graph Embeddings based Approach for Author Name Disambiguation using Literals
Cristian Santini, Genet Asefa Gesese, Silvio Peroni +3
Scholarly data is growing continuously containing information about the articles from a plethora of venues including conferences, journals, etc. Many initiatives have been taken to…