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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Veröffentlicht in:	IEEE transactions on industrial informatics Jg. 18; H. 2; S. 1231 - 1239
Hauptverfasser:	Xing, Yongheng, Hu, Liang, Zhang, Xiaolu, Wu, Gang, Wang, Feng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.02.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	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
Online-Zugang:	Volltext
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