CCDF-TAP: A Context-Aware Conflict Detection Framework for IoT Trigger-Action Programming With Graph Neural Network

The rapid expansion of the Internet of Things (IoT) has led to the development of smart homes and automation systems. Trigger-action programming (TAP) has emerged as a prevalent paradigm used in IoT, facilitating the creation of automation rules. However, with the proliferation of TAP rules, the pot...

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Vydané v:	IEEE internet of things journal Ročník 11; číslo 19; s. 31534 - 31544
Hlavní autori:	Xing, Yongheng, Hu, Liang, Du, Xinqi, Shen, Zhiqi, Hu, Juncheng, Wang, Feng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.10.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Automation Conflict detection Context Data mining graph neural network (GNN) Graph neural networks Internet of Things Internet of Things (IoT) Programming Security Smart buildings Smart homes Smart houses trigger-action programming (TAP)
ISSN:	2327-4662, 2327-4662
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