Nonnegative Matrix Factorization Based Heterogeneous Graph Embedding Method for Trigger-Action Programming in IoT

Nowadays, users can personalize Internet of Things (IoT) devices/web services via trigger-action programming (TAP). As the number of connected entities grows, the relations of triggers and actions become progressively complex (i.e., the heterogeneity of TAP), which becomes a challenge for existing m...

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Vydané v:	IEEE transactions on industrial informatics Ročník 18; číslo 2; s. 1231 - 1239
Hlavní autori:	Xing, Yongheng, Hu, Liang, Zhang, Xiaolu, Wu, Gang, Wang, Feng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.02.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Artificial intelligence Cameras Data mining Embedding Factorization Feature extraction Graph embedding Heterogeneity heterogeneous information networks Internet of Things Internet of Things (IoT) Machine learning nonnegative matrix factorization Programming Semantics trigger-action programming (TAP) Web services
ISSN:	1551-3203, 1941-0050
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