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• W2148945759 abstract "We develop a framework to track the structure of temporal networks with a signal processing approach. The method is based on the duality between networks and signals using a multidimensional scaling technique. This enables a study of the network structure using frequency patterns of the corresponding signals. An extension is proposed for temporal networks, thereby enabling a tracking of the network structure over time. A method to automatically extract the most signicant frequency patterns and their activation coecients over time is then introduced, using nonnegative matrix factorization of the temporal spectra. The framework, inspired by audio decomposition, allows transforming back these frequency patterns into networks, to highlight the evolution of the underlying structure of the network over time. The eectiveness of the method is rst evidenced on a toy example, prior being used to study a temporal network of face-to-face contacts. The extraction of sub-networks highlights signicant structures decomposed on time intervals." @default.
• W2148945759 created "2016-06-24" @default.
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• W2148945759 date "2015-05-12" @default.
• W2148945759 modified "2023-09-27" @default.
• W2148945759 title "Duality between Temporal Networks and Signals: Extraction of the Temporal Network Structures" @default.
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• W2148945759 hasPublicationYear "2015" @default.
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