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 / Pinto, Agnese; Di Sciascio, Eugenio; Ruta, Michele. - ELETTRONICO. - 926:(2012), pp. 38-42. (Intervento presentato al convegno Doctoral Consortium of the 12th AI*IA Symposium on Artificial Intelligence: AIxIA-DC 2012 tenutosi a Roma, Italy nel June 15, 2012).
Machine Learning Methods and Technologies for Ubiquitous Computing
Agnese Pinto;Eugenio Di Sciascio;Michele Ruta
2012-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
