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Time Prediction on Temporal Knowledge Graphs

Roxana Pop ( University of Oslo )

Temporal Knowledge Graphs (TKGs) are an extension of Knowledge Graphs where facts are temporally scoped. They have recently received increasing attention in knowledge management, mirroring an increased interest in temporal graph learning within the graph learning research area. Roxana will give an overview of the tasks approached in the TKG learning community and focus on the time prediction task. She will also discuss ideas for a neurosymbolic framework connecting neural networks and DatalogMTL.

 

 

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