RTFE: A Recursive Temporal Fact Embedding Framework for Temporal Knowledge Graph Completion

Understand

Static knowledge graph (SKG) embedding (SKGE) has been studied intensively in the past years.

• Recently, temporal knowledge graph (TKG) embedding (TKGE) has emerged.
• In this paper, we propose a Recursive Temporal Fact Embedding (RTFE) framework to transplant SKGE models to TKGs and to enhance the performance of existing TKGE models for TKG completion.
• Different from previous work which ignores the continuity of states of TKG in time evolution, we treat the sequence of graphs as a Markov chain, which transitions from the previous state to the next state.