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TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion
[article]
2021
arXiv
pre-print
Reasoning in a temporal knowledge graph (TKG) is a critical task for information retrieval and semantic search. It is particularly challenging when the TKG is updated frequently. The model has to adapt to changes in the TKG for efficient training and inference while preserving its performance on historical knowledge. Recent work approaches TKG completion (TKGC) by augmenting the encoder-decoder framework with a time-aware encoding function. However, naively fine-tuning the model at every time
arXiv:2104.08419v3
fatcat:sx6nodkoivgnbnkw6ip43wxn5q