Big Data Series Analytics in the Context of Environmental Crowd Sensing
| Autor: | Hafsa El Hafyani |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
business.industry
Process (engineering) Computer science Online analytical processing 010401 analytical chemistry Big data Context (language use) 01 natural sciences Data science 0104 chemical sciences Activity recognition 03 medical and health sciences 0302 clinical medicine Knowledge extraction Analytics Data analysis 030212 general & internal medicine business |
| Zdroj: | MDM |
| DOI: | 10.1109/mdm48529.2020.00056 |
| Popis: | The new mobile crowd sensing (MCS) paradigm leads to the generation of a large amount of data originated from different sources. The inhomogeneous nature of produced data turns the process of data analytics and knowledge extraction extremely challenging and complicated. More specifically, mining such data needs special care and processing. In this paper, we focus on the analysis, processing, and exploration of such data. We advocate this process should benefit from the diverse data sources in the MCS context, including user’s annotation and various ambient data collected through sensors. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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