The research proposal concerns the use of machine learning techniques for data mining in pervasive environments. It will lead to the formalization of a framework, able to translate series of "raw" data in high-level knowledge. Novel machine learning approaches, interpreting data coming from the environment that surrounds users, will be liver- Aged. Data will be collected through micro-components deployed in the field and will be processed for the identification and characterization of phenomena and contexts. Eventually they will be semantically annotated to support futher application-level logic-based reasoning and knowledge discovery.

Machine Learning Methods and Technologies for Ubiquitous Computing

Agnese Pinto;Eugenio Di Sciascio;Michele Ruta
2012

Abstract

The research proposal concerns the use of machine learning techniques for data mining in pervasive environments. It will lead to the formalization of a framework, able to translate series of "raw" data in high-level knowledge. Novel machine learning approaches, interpreting data coming from the environment that surrounds users, will be liver- Aged. Data will be collected through micro-components deployed in the field and will be processed for the identification and characterization of phenomena and contexts. Eventually they will be semantically annotated to support futher application-level logic-based reasoning and knowledge discovery.
Doctoral Consortium of the 12th AI*IA Symposium on Artificial Intelligence: AIxIA-DC 2012
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/52528
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