A Recommendation System for Trigger–Action Programming Rules via Graph Contrastive Learning

Trigger–action programming (TAP) enables users to automate Internet of Things (IoT) devices by creating rules such as “IF Device1.TriggerState is triggered, THEN Device2.ActionState is executed”. As the number of IoT devices grows, the combination space between the functions provided by devices expa...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Sensors (Basel, Switzerland) Ročník 24; číslo 18; s. 6151
Hlavní autori:	Kuang, Zhejun, Xiong, Xingbo, Wu, Gang, Wang, Feng, Zhao, Jian, Sun, Dawen
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland MDPI AG 23.09.2024 MDPI
Predmet:	Automation Collaboration Computational linguistics Efficiency End users graph contrastive learning Internet of Things Language processing Natural language interfaces Recommender systems rule recommendation Semantics trigger–action programming Web applications trigger–action programming rule recommendation graph contrastive learning Internet of Things
ISSN:	1424-8220, 1424-8220
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!