Results 11 to 20 of about 8,673 (229)
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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Diachronic Embedding for Temporal Knowledge Graph Completion
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 Knowledge graphs (KGs) typically contain temporal facts indicating relationships among entities at different times. Due to their incompleteness, several approaches have been proposed to infer new facts for a KG based on the existing ones–a problem known as KG completion.
Rishab Goel +3 more
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Applied Sciences, 2023 Temporal knowledge graph completion (TKGC) refers to the prediction and filling in of missing facts on time series, which is essential for many downstream applications.
Minwei Wen +3 more
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TBRm: A Time Representation Method for Industrial Knowledge Graph
Applied Sciences, 2022 With the development of the artificial intelligence industry, Knowledge Graph (KG), as a concise and intuitive data presentation form, has received extensive attention and research from both academia and industry in recent years.
Keyan Cao, Chuang Zheng
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Search to Pass Messages for Temporal Knowledge Graph Completion
Findings of the Association for Computational Linguistics: EMNLP 2022, 2022 Completing missing facts is a fundamental task for temporal knowledge graphs (TKGs). Recently, graph neural network (GNN) based methods, which can simultaneously explore topological and temporal information, have become the state-of-the-art (SOTA) to complete TKGs.
Zhen Wang 0004 +3 more
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Proceedings of the 11th Knowledge Capture Conference, 2021 Almost all statements in knowledge bases have a temporal scope during which they are valid. Hence, knowledge base completion (KBC) on temporal knowledge bases (TKB), where each statement \textit{may} be associated with a temporal scope, has attracted growing attention.
Ling Cai 0002 +4 more
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JOINT FEATURES-BASED KNOWLEDGE GRAPH COMPLETION [PDF]
International Journal of Intelligent Computing and Information SciencesKnowledge graphs (KGs) help in resolving data inconsistencies and redundancies by organizing information in a unified structure, paving the way for building scalable, interpretable AI systems, as they provide a transparent way to trace reasoning paths ...
Maha Farghaly +2 more
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Learning Sequence Encoders for Temporal Knowledge Graph Completion [PDF]
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 2018 Research on link prediction in knowledge graphs has mainly focused on static multi-relational data. In this work we consider temporal knowledge graphs where relations between entities may only hold for a time interval or a specific point in time. In line with previous work on static knowledge graphs, we propose to address this problem by learning ...
Alberto García-Durán +2 more
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Hyperplane-based time-aware knowledge graph embedding for temporal knowledge graph completion
Journal of Intelligent & Fuzzy Systems, 2022 Knowledge Graph (KG) embedding approaches have been proved effective to infer new facts for a KG based on the existing ones–a problem known as KG completion. However, most of them have focused on static KGs, in fact, relational facts in KGs often show temporal dynamics, e.g., the fact (US, has president, Barack Obama, [2009–2017]) is only valid from ...
Peng He +4 more
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A Survey on Temporal Knowledge Graph Completion: Taxonomy, Progress, and Prospects
CoRR, 2023 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. However, TKGs often suffer from incompleteness for three main reasons: the continuous emergence of new knowledge, the weakness of the algorithm for extracting ...
Jiapu Wang +10 more
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