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SUMMARY:Networks as signals: Extraction of dynamical network structures - 
 Pierre Borgnat (ENS - Lyon\; CNRS (Centre national de la recherche scienti
 fique))
DTSTART:20161214T140000Z
DTEND:20161214T144500Z
UID:TALK69496@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Joint work with Ronan Hamon (LIF\, Marseille\, France)\, P. Fl
 andrin (CNRS\, LP\, ENS de Lyon\, France) and C. Robardet (LIRIS\, INSA de
  Lyon\, France)<br>We have proposed &nbsp\;a<span>&nbsp\;new framework to 
 track the structure of temporal networks\, using&nbsp\;a signal processing
  approach: the method is based on the duality between static networks and 
 signals using a multidimensional scaling technique. For temporal networks\
 , it enables&nbsp\;a tracking of the network structure over time. To extra
 ct the most significant patterns of the networks&nbsp\;and their activatio
 n over time\, we use&nbsp\;nonnegative matrix factorization of the tempora
 l spectra. This framework\, inspired by audio decomposition\, allows trans
 forming back these frequency patterns into networks\, so as&nbsp\;to highl
 ight the evolution of the underlying structure of the network over time. T
 he effectiveness of the method is first evidenced on a toy example\, prior
  being used to study a temporal network of face-to-face contacts. The extr
 action of sub-networks highlights significant structures decomposed on tim
 e intervals.&nbsp\; 				 			 		</span>
LOCATION:Seminar Room 1\, Newton Institute
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