Temporal Knowledge Graph Completion
20 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Temporal Knowledge Graph Completion
Most implemented papers
Along the Time: Timeline-traced Embedding for Temporal Knowledge Graph Completion
zhangfw123/TLT-KGE
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The 31st ACM International Conference on Information and Knowledge Management (CIKM) 2022
In order to represent the facts happening in a specific time, temporal knowledge graph (TKG) embedding approaches are put forward.
Search to Pass Messages for Temporal Knowledge Graph Completion
striderdu/spa
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In particular, we develop a generalized framework to explore topological and temporal information in TKGs.
Logic and Commonsense-Guided Temporal Knowledge Graph Completion
ngl567/lcge
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To address these challenges, we propose a Logic and Commonsense-Guided Embedding model (LCGE) to jointly learn the time-sensitive representation involving timeliness and causality of events, together with the time-independent representation of events from the perspective of commonsense.
Improving Few-Shot Inductive Learning on Temporal Knowledge Graphs using Confidence-Augmented Reinforcement Learning
Most previous TKGC methods only consider predicting the missing links among the entities seen in the training set, while they are unable to achieve great performance in link prediction concerning newly-emerged unseen entities.
Pre-trained Language Model with Prompts for Temporal Knowledge Graph Completion
jaysaligia/ppt
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We train our model with a masking strategy to convert TKGC task into a masked token prediction task, which can leverage the semantic information in pre-trained language models.
A Survey on Temporal Knowledge Graph Completion: Taxonomy, Progress, and Prospects
Temporal characteristics are prominently evident in a substantial volume of knowledge, which underscores the pivotal role of Temporal Knowledge Graphs (TKGs) in both academia and industry.
Leveraging Pre-trained Language Models for Time Interval Prediction in Text-Enhanced Temporal Knowledge Graphs
Most knowledge graph completion (KGC) methods learn latent representations of entities and relations of a given graph by mapping them into a vector space.
Re-Temp: Relation-Aware Temporal Representation Learning for Temporal Knowledge Graph Completion
adlnlp/re-temp
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Temporal Knowledge Graph Completion (TKGC) under the extrapolation setting aims to predict the missing entity from a fact in the future, posing a challenge that aligns more closely with real-world prediction problems.
Mitigating Heterogeneity among Factor Tensors via Lie Group Manifolds for Tensor Decomposition Based Temporal Knowledge Graph Embedding
dellixx/tkbc-lie
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Recent studies have highlighted the effectiveness of tensor decomposition methods in the Temporal Knowledge Graphs Embedding (TKGE) task.
