Mining Big Data is among one of the most attracting research contexts of recent years. Essentially, mining Big Data puts emphasis on how classical Data Mining algorithms can be extended in order to deal with novel features of Big Data, such as volume, variety and velocity. This novel challenge opens the door to a widespread number of challenging research problems that will generate both academic and industrial spin-offs in future years. Following this main trend, in this paper we provide a brief discussion on most relevant open problems and future directions on the fundamental issue of mining Big Data.
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Titolo: | Big data mining or turning data mining into predictive analytics from large-scale 3vs data: The future challenge for knowledge discovery |
Autori: | |
Data di pubblicazione: | 2014 |
Abstract: | Mining Big Data is among one of the most attracting research contexts of recent years. Essentially, mining Big Data puts emphasis on how classical Data Mining algorithms can be extended in order to deal with novel features of Big Data, such as volume, variety and velocity. This novel challenge opens the door to a widespread number of challenging research problems that will generate both academic and industrial spin-offs in future years. Following this main trend, in this paper we provide a brief discussion on most relevant open problems and future directions on the fundamental issue of mining Big Data. |
Handle: | http://hdl.handle.net/20.500.11770/312759 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |