Temporal knowledge graphs, also known as episodic or time-dependent knowledge graphs, are largescale 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.
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