Data-driven scientific discovery is a key emerging paradigm driving research innovation and industrial development in domains such as business, social sci­ence, the Internet of Things, and cloud computing. The field encompasses the larger ar­eas of data analytics, machine learning, and managing big data, while related new sci­entific chal­lenges range from data capture, creation, storage, search, sharing, analysis, and vis­ualization, to integration across heterogeneous, interdependent complex resources for real-time decision-making, collaboration, and value creation. The journal welcomes experimental and theoretical findings on data science and advanced analytics along with their applications to real-life situations

An analytical framework to nowcast well-being using mobile phone data

PAPPALARDO, LUCA;GABRIELLI, LORENZO;PEDRESCHI, DINO;GIANNOTTI, FOSCA
2016-01-01

Abstract

Data-driven scientific discovery is a key emerging paradigm driving research innovation and industrial development in domains such as business, social sci­ence, the Internet of Things, and cloud computing. The field encompasses the larger ar­eas of data analytics, machine learning, and managing big data, while related new sci­entific chal­lenges range from data capture, creation, storage, search, sharing, analysis, and vis­ualization, to integration across heterogeneous, interdependent complex resources for real-time decision-making, collaboration, and value creation. The journal welcomes experimental and theoretical findings on data science and advanced analytics along with their applications to real-life situations
2016
Pappalardo, Luca; Vanhoof, Maarten; Gabrielli, Lorenzo; Smoreda, Zbigniew; Pedreschi, Dino; Giannotti, Fosca
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/833985
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