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Temporal Knowledge Graph Completion: A Survey [PDF]
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023 Knowledge graph completion (KGC) predicts missing links and is crucial for real-life knowledge graphs, which widely suffer from incompleteness. KGC methods assume a knowledge graph is static, but that may lead to inaccurate prediction results because many facts in the knowledge graphs change over time.
Borui Cai +5 more
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Temporal knowledge graph reasoning using global and recent history information [PDF]
Scientific ReportsSince the static Knowledge Graph cannot meet the dynamics of knowledge in the real world, Temporal Knowledge Graph has become a potential method for processing temporal knowledge.
Changlong Wang +10 more
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AugGKG: a grid-augmented geographic knowledge graph representation and spatio-temporal query model
International Journal of Digital Earth, 2023 As an emerging knowledge representation model in the domain of knowledge graphs, geographic knowledge graph can take full advantage of semantic, spatial and temporal information to facilitate answering spatio-temporal questions and completing relations ...
Bing Han +6 more
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Learning temporal granularity with quadruplet networks for temporal knowledge graph completion [PDF]
Scientific ReportsTemporal Knowledge Graphs (TKGs) capture the dynamic nature of real-world facts by incorporating temporal dimensions that reflect their evolving states. These variations add complexity to the task of knowledge graph completion.
Rushan Geng, Cuicui Luo
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Multi-Modal Spatio-Temporal Knowledge Graph of Ship Management
Applied Sciences, 2023 In modern maritime activities, the quality of ship communication directly impacts the safety, efficiency, and economic viability of ship operations. Therefore, predicting and analyzing ship communication status has become a crucial task to ensure the ...
Yitao Zhang +7 more
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Temporal Knowledge Graph Representation Learning [PDF]
Jisuanji kexue, 2022 As a structured form of human knowledge,knowledge graphs have played a great supportive role in supporting the semantic intercommunication of massive,multi-source,heterogeneous data,and effectively support tasks such as data analysis,attracting the ...
XU Yong-xin, ZHAO Jun-feng, WANG Ya-sha, XIE Bing, YANG Kai
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Temporal RDF Modeling Based on Relational Database [PDF]
Jisuanji kexue, 2022 With the increase of temporal data,the concept of temporal knowledge graph is popularized,and how to represent temporal knowledge graph efficiently has become an important research direction.Although resource description framework(RDF) is widely used in ...
HAN Xiao, ZHANG Zhe-qing, YAN Li
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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
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Embedding Uncertain Temporal Knowledge Graphs
Mathematics, 2023 Knowledge graph (KG) embedding for predicting missing relation facts in incomplete knowledge graphs (KGs) has been widely explored. In addition to the benchmark triple structural information such as head entities, tail entities, and the relations between
Tongxin Li +5 more
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Active Temporal Knowledge Graph Alignment
International Journal on Semantic Web and Information Systems, 2023 Entity alignment aims to identify equivalent entity pairs from different knowledge graphs (KGs). Recently, aligning temporal knowledge graphs (TKGs) that contain time information has aroused increasingly more interest, as the time dimension is widely used in real-life applications. The matching between TKGs requires seed entity pairs, which are lacking
Jie Zhou +3 more
openaire +1 more source