Machine learning-based approaches for large-scale temporal data analytics
In many domains such as telecommunications, finance and sensor monitoring, large volumes of unlabeled temporal data are continuously generated in a sequential format, where the timestamps of the generated records are available. From a data analysis standpoint, there is significant utility to be gai...
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| Format: | Thesis |
| Language: | English |
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2019
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| Online Access: | https://hdl.handle.net/10356/105859 http://hdl.handle.net/10220/47870 https://doi.org/10.32657/10220/47870 |