User intention prediction for trigger-action programming rule using multi-view representation learning

Trigger-action programming (TAP) allows users to create rules for automating smart devices and Internet services, such as “If a person is leaving, then turn off the air conditioner”. User intention, as the internal driving force behind rule creation, plays a crucial role in understanding user demand...

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Vydáno v:	Expert systems with applications Ročník 267; s. 126198
Hlavní autoři:	Wu, Gang, Hu, Liang, Hu, Yuxiao, Xing, Yongheng, Wang, Feng
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.04.2025
Témata:	Internet of Things Multi-view representation learning Trigger-action programming User intention prediction Multi-view representation learning Trigger-action programming User intention prediction Internet of Things
ISSN:	0957-4174
On-line přístup:	Získat plný text
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