Results 181 to 190 of about 8,673 (229)

Unlocking electronic health records: a hybrid graph RAG approach to safe clinical AI for patient QA. [PDF]

Front Digit Health
Thio S, Lewis M, Denaxas S, Dobson RJB.
europepmc   +1 more source

Data compression of Bridge Resilience Control: Algorithm and case analysis. [PDF]

PLoS One
Chen M.
europepmc   +1 more source

Cross-modal adaptive reconstruction of open education resources. [PDF]

Sci Rep
Shengju T, Li F, Wang Z, Zhaoyuan X.
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Tackling Long-Tail Entities for Temporal Knowledge Graph Completion

Companion Proceedings of the ACM Web Conference 2024
Mehrnoosh Mirtaheri, Ryan A. Rossi, Sungchul Kim, Kanak Mahadik, Tong Yu 0001, Xiang Chen 0010, Mohammad Rostami   +6 more
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Computational approaches for drug-drug interaction prediction: a systematic review of data sources, modeling strategies, and evaluation frameworks. [PDF]

Front Pharmacol
Hashir Q, Asfand E Yar M, Ullah A, Kamal S, Ullah F, Abdullah ZH.   +5 more
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Real-time human progress estimation with online dynamic time warping for collaborative robotics. [PDF]

Front Robot AI
De Lazzari D, Terreran M, Giacomuzzo G, Jain S, Falco P, Carli R, Ghidoni S, Romeres D.   +7 more
europepmc   +1 more source

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Spatial-Temporal Attention Network for Temporal Knowledge Graph Completion

Lecture Notes in Computer Science, 2021
Temporal knowledge graph completion, which aims to predict missing links in temporal knowledge graph (TKG), is an important research task due to the incompleteness of TKG. Recently, TKG embedding methods have proved to be effective for this task. However, most of existing methods regard TKG as a set of independent facts and consequently ignore the ...
Jie Shao
exaly   +2 more sources

Temporal-structural importance weighted graph convolutional network for temporal knowledge graph completion

Future Generation Computer Systems, 2023
Xin Bi, Xiangguo Zhao
exaly   +2 more sources

QDN: A Quadruplet Distributor Network for Temporal Knowledge Graph Completion

IEEE Transactions on Neural Networks and Learning Systems
Temporal knowledge graph completion (TKGC) is an extension of the traditional static knowledge graph completion (SKGC) by introducing the timestamp. The existing TKGC methods generally translate the original quadruplet to the form of the triplet by integrating the timestamp into the entity/relation, and then use SKGC methods to infer the missing item ...
Junbin Gao, Boyue Wang, Yongli Hu
exaly   +3 more sources