Results 11 to 20 of about 69,930 (266)
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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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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Spatio-Temporal Graph for Video Captioning With Knowledge Distillation [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 CVPR ...
Boxiao Pan +6 more
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Event-Centric Temporal Knowledge Graph Construction: A Survey
Mathematics, 2023 Textual documents serve as representations of discussions on a variety of subjects. These discussions can vary in length and may encompass a range of events or factual information.
Timotej Knez, Slavko Žitnik
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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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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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A Spatial-Temporal Graph Mining Algorithm Based on Spatial-Temporal Sparse Attention [PDF]
Jisuanji gongcheng, 2023 Existing spatial-temporal graph mining algorithms are typically based on static graph structures, which are pre-defined by experts or constructed via feature augmentation.These static graph structures rely on subjective prior knowledge and are not easily
XIE Yi, WANG Qiang, LI Haihong, JIN Cheng, REN Hongrun, XUE Wen, XIONG Yun
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Survey on Construction Method of Temporal Knowledge Graph [PDF]
Jisuanji kexue yu tansuoAs a bridge connecting data, knowledge, and intelligence, knowledge graph has been widely applied in fields such as search assistance, intelligent recommendation, question-answering systems, and natural language processing. However, with the expansion of
LU Jiamin, ZHANG Jing, FENG Jun, AN Qi
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Modeling the evolution of temporal knowledge graphs with uncertainty
CoRR, 2023 Forecasting future events is a fundamental challenge for temporal knowledge graphs (tKG). As in real life predicting a mean function is most of the time not sufficient, but the question remains how confident can we be about our prediction? Thus, in this work, we will introduce a novel graph neural network architecture (WGP-NN) employing (weighted ...
Soeren Nolting +2 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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