Papers by Dezhi Hong
SeNsER: Learning Cross-Building Sensor Metadata Tagger (2020.findings-emnlp)
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| Challenge: | Sensor metadata tagging is a key component of smart building applications. |
| Approach: | They propose a framework that learns a sensor metadata tagger for a new building based on its raw metadata and some existing fully annotated building. |
| Outcome: | The proposed framework learns a sensor metadata tagger for a new building based on its raw metadata and some existing fully annotated building. |
Sensei: Self-Supervised Sensor Name Segmentation (2021.findings-acl)
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| Challenge: | Sensor names are alphanumeric strings that encode key contextual information such as their function or physical location. |
| Approach: | They propose a self-supervised framework that can learn to segment sensor names without human annotation. |
| Outcome: | The proposed framework can learn to segment sensor names without human annotation on buildings. |