Cai, Z;
De, S;
Kedziora, M;
Wang, C;
(2022)
Guest Editorial Special Issue on Graph-Powered Machine Learning for Internet of Things.
IEEE Internet of Things Journal
, 9
(12)
pp. 9102-9105.
10.1109/JIOT.2022.3164812.
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Abstract
Internet of Things (IoT) refers to an ecosystem where applications and services are driven by data collected from devices interacting with each other and the physical world. Although IoT has already brought spectacular benefits to human society, the progress is actually not as fast as expected. From network structures to control flow graphs, IoT naturally generates an unprecedented volume of graph data continuously, which stimulates fertilization and making use of advanced graph-powered methods on the diverse, dynamic, and large-scale graph IoT data.
| Type: | Article |
|---|---|
| Title: | Guest Editorial Special Issue on Graph-Powered Machine Learning for Internet of Things |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/JIOT.2022.3164812 |
| Publisher version: | http://dx.doi.org/10.1109/JIOT.2022.3164812 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Social Research Institute UCL > Provost and Vice Provost Offices > School of Education UCL |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10156924 |
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