Learning With Temporal Knowledge Graphs

MCML Authors

Yunpu Ma

Dr.

→ Group Volker Tresp
 Database Systems, Data Mining and AI
→ Co-Group Hinrich Schütze

Volker Tresp

Prof. Dr.

Core PI

Database Systems, Data Mining and AI

Abstract

Temporal knowledge graphs, also known as episodic or time-dependent knowledge graphs, are large-scale event databases that describe temporally evolving multi-relational data. An episodic knowledge graph can be regarded as a sequence of semantic knowledge graphs incorporated with timestamps. In this talk, we review recently developed learning-based algorithms for temporal knowledge graphs completion and forecasting.

inproceedings MHT20

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Workshop @CIKM 2020

Workshop at the 29th ACM International Conference on Information and Knowledge Management. Galway, Ireland, Oct 19-23, 2020. Invited Talk.

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Authors

Y. Ma • Z. Han • V. Tresp

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Links

PDF

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In Collaboration

 Siemens AG

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Research Area

 A3 | Computational Models