To address this problem, this paper proposes two SpatioTemporal-aware knowledge graph completion models based on the Sequence Encoder, namely STSE and S-TSE, ...
Nov 9, 2022 · To address this problem, this paper proposes two Spatio Temporal-aware knowledge graph completion models based on the Sequence Encoder, namely ...
Static knowledge graph completion mainly consists of two steps: knowledge graph embedding and scoring function, which aims to learn the represen- tations of ...
We learn time-aware represen- tations by training a recursive neural network with sequences of tokens representing the time predi- cate and the digits of the ...
Missing: Spatiotemporal | Show results with:Spatiotemporal
This work utilizes recurrent neural networks to learn time-aware representations of relation types which can be used in conjunction with existing latent ...
Missing: Spatiotemporal | Show results with:Spatiotemporal
Our study fills the gap in knowledge completion techniques in the field of STKG. We present a model for completion based on the well-known tensor factorization ...
Spatiotemporal knowledge graph completion via diachronic and ...
dl.acm.org › doi › j.ins.2024.120477
Jul 9, 2024 · Our study fills the gap in knowledge completion techniques in the field of STKG. We present a model for completion based on the well-known ...
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This article proposes a fine-grained fuzzy spatiotemporal RDF model, which provides the underlying representation framework for FSTRE, and shows that the ...
Feb 19, 2024 · Learn- ing sequence encoders for temporal knowledge graph completion. ... Tensor de- compositions for temporal knowledge base completion.
We evaluate our model and baselines on five real-world TKGs that have been widely used in previous studies, i.e., ICEWS14 [7], ICEWS05-15 [7] and GDELT [15].