Attention-Aware Encoder-Decoder Neural Networks for Heterogeneous Graphs of Things

Recent trend focuses on using heterogeneous graph of things (HGoT) to represent things and their relations in the Internet of Things, thereby facilitating the applying of advanced learning frameworks, i.e., deep learning (DL). Nevertheless, this is a challenging task since the existing DL models are...

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Vydané v:	IEEE transactions on industrial informatics Ročník 17; číslo 4; s. 2890 - 2898
Hlavní autori:	Li, Yangfan, Chen, Cen, Duan, Mingxing, Zeng, Zeng, Li, Kenli
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.04.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Coders Computer architecture Decoding Encoding Fuses Graph neural network (GNN) Graph neural networks graph of things heterogeneous graph Informatics Internet of Things Internet of Things (IoT) Neural networks Nodes Semantics
ISSN:	1551-3203, 1941-0050
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