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

IEEE Transactions on Industrial Informatics(2022)

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摘要
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 models to completely preserve the heterogeneous data and semantic information in trigger and action. ...
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关键词
Internet of Things,Semantics,Programming,Feature extraction,Cameras,Data mining,Machine learning
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