Temporal inductive path neural network for temporal knowledge graph reasoning
Artificial IntelligenceAccepted to Artificial ...
Meng Xiao +2 more
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Dynamic Evolution and Relation Perception for Temporal Knowledge Graph Reasoning
Future InternetTemporal knowledge graphs (TKGs) incorporate temporal information into traditional triplets, enhancing the dynamic representation of real-world events.
Yuan Huang +3 more
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CALENDAR+: in-context contrastive learning for temporal knowledge graph reasoning
Complex & Intelligent SystemsTemporal Knowledge Graph (TKG) reasoning aims to infer future events from historical facts. Recent advances in large language models (LLMs) have shown that in-context learning can effectively enhance temporal reasoning.
Xingyi Li +4 more
doaj +2 more sources
Extrapolation Reasoning on Temporal Knowledge Graphs via Temporal Dependencies Learning
CAAI Transactions on Intelligence TechnologyExtrapolation on Temporal Knowledge Graphs (TKGs) aims to predict future knowledge from a set of historical Knowledge Graphs in chronological order. The temporally adjacent facts in TKGs naturally form event sequences, called event evolution patterns ...
Ye Wang +5 more
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Temporal knowledge graph reasoning triggered by memories
Applied Intelligence, 2023 Inferring missing facts in temporal knowledge graphs is a critical task and has been widely explored. Extrapolation in temporal reasoning tasks is more challenging and gradually attracts the attention of researchers since no direct history facts for prediction.
Mengnan Zhao 0001 +3 more
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MSEN: A Multi-Scale Evolutionary Network for Modeling the Evolution of Temporal Knowledge Graphs
Future Internet, 2023 Temporal knowledge graphs play an increasingly prominent role in scenarios such as social networks, finance, and smart cities. As such, research on temporal knowledge graphs continues to deepen.
Yong Yu +5 more
doaj +1 more source
A geographic knowledge integrated computation framework based on grid graph modelling [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information SciencesManaging dynamic geographic knowledge effectively is hindered by fragmented tools lacking holistic integration, particularly when handling the heterogeneous and evolving nature of real world spatio-temporal data.
B. Han, B. Han, T. Qu
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A temporal knowledge graph reasoning model based on recurrent encoding and contrastive learning [PDF]
PeerJ Computer ScienceTemporal knowledge graphs (TKGs) are critical tools for capturing the dynamic nature of facts that evolve over time, making them highly valuable in a broad spectrum of intelligent applications.
Weitong Liu +4 more
doaj +2 more sources
Recurrent Event Networks Based on Subgraph and Attention Enhancement
IEEE Access, 2023 Temporal knowledge graph (TKG) reasoning, as an essential research direction in natural language processing, focuses on capturing the dynamic changes in entities and relationships over time.
Hongxi Liu, Jiana Meng, Shichang Sun
doaj +1 more source
Temporal Knowledge Graph Reasoning with Historical Contrastive Learning
Proceedings of the AAAI Conference on Artificial Intelligence, 2023 Temporal knowledge graph, serving as an effective way to store and model dynamic relations, shows promising prospects in event forecasting. However, most temporal knowledge graph reasoning methods are highly dependent on the recurrence or periodicity of events, which brings challenges to inferring future events related to entities that lack historical ...
Yi Xu 0004 +3 more
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