Meaningful selection of temporal resolution for dynamic networks
作者： Rajmonda Sulo , Tanya Berger-Wolf , Robert Grossman
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摘要: The understanding of dynamics data streams is greatly affected by the choice temporal resolution at which are discretized, aggregated, and analyzed. Our paper focuses explicitly on represented as dynamic networks. We propose a framework for identifying meaningful levels that best reveal critical changes in network structure, balancing reduction noise with loss information. demonstrate applicability our approach analyzing various statistics both synthetic real networks using those to detect important events structure.
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