Results 11 to 20 of about 48,760 (297)
Embedding Uncertain Temporal Knowledge Graphs [PDF]
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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Question Answering Over Temporal Knowledge Graphs [PDF]
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), 2021 Temporal Knowledge Graphs (Temporal KGs) extend regular Knowledge Graphs by providing temporal scopes (start and end times) on each edge in the KG. While Question Answering over KG (KGQA) has received some attention from the research community, QA over Temporal KGs (Temporal KGQA) is a relatively unexplored area.
Apoorv Saxena +2 more
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Revolutionary Strategy for Depicting Knowledge Graphs with Temporal Attributes [PDF]
MathematicsIn practical applications, the temporal completeness of knowledge graphs is of great importance. However, previous studies have mostly focused on static knowledge graphs, generally neglecting the dynamic evolutionary properties of facts.
Sihan Li, Qi Li
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Modelling temporal data in knowledge graphs: a systematic review protocol [version 2; peer review: 1 approved, 2 approved with reservations] [PDF]
HRB Open Research, 2022 Background: The benefits of having high-quality healthcare data are well established. However, high-dimensionality and irregularity of healthcare data pose challenges in their management. Knowledge graphs have gained increasing popularity in many domains,
Sepideh Hooshafza +5 more
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Unsupervised Entity Alignment for Temporal Knowledge Graphs [PDF]
CoRR, 2023 Entity alignment (EA) is a fundamental data integration task that identifies equivalent entities between different knowledge graphs (KGs). Temporal Knowledge graphs (TKGs) extend traditional knowledge graphs by introducing timestamps, which have received increasing attention.
Xiaoze Liu +4 more
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Summarizing Entity Temporal Evolution in Knowledge Graphs [PDF]
Companion Proceedings of The 2019 World Wide Web Conference, 2019 Companion Proceedings of The 2019 World Wide Web Conference on - WWW '19 The 2019 World Wide Web Conference, WWW '19, San Francisco, USA, 13 May 2019 - 17 May 2019; New York, NY : ACM Press 961-965 (2019).
Mayesha Tasnim +4 more
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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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Complex Temporal Question Answering on Knowledge Graphs [PDF]
Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 2021 Question answering over knowledge graphs (KG-QA) is a vital topic in IR. Questions with temporal intent are a special class of practical importance, but have not received much attention in research. This work presents EXAQT, the first end-to-end system for answering complex temporal questions that have multiple entities and predicates, and associated ...
Zhen Jia 0002 +3 more
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Data, 2023 Temporal knowledge graphs can be used to represent the current state of the world and, as daily events happen, the need to update the temporal knowledge graph, in order to stay consistent with the state of the world, becomes very important.
Ryan Ong +3 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
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