Personalized management of semantic, dynamic data in pervasive systems: Context-ADDICT revisited
High Performance Computing & Simulation(2014)
摘要
Due to the high information load to which everyone is exposed in her everyday life, the rise of new, systems fully supporting pervasive information distribution, analysis and sharing becomes a key factor to allow a correct and useful interaction among humans and computer systems. This kind of systems must allow to manage, integrate, analyze, and possibly reason on, a large and heterogeneous set of data. The SuNDroPS system, briefly described in this paper, applies context-aware techniques to data gathering, shared services, and information distribution; the system is based on a context-aware approach that, applied to these tasks, leads to the reduction of the so-called information noise, delivering to the users only the portion of information that is useful in their current context.
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关键词
data handling,ubiquitous computing,Context-ADDICT system,SuNDroPS system,context-aware techniques,data gathering,dynamic data,information analysis,information noise,information sharing,personalized data management,pervasive information distribution,pervasive systems,semantic data,Complex Event Processing,Context-Aware Data Management,Data-stream Processing,Map-Reduce-based Data Mining Algorithms
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