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Data Mining, Networks and Dynamics (Dagstuhl Seminar 11451)

Authors: Lars Elden and Andreas Frommer

Published in: Dagstuhl Reports, Volume 1, Issue 11 (2012)

In many areas one needs to extract relevant information from signals generated by dynamical systems evolving on networks with a configuration that itself evolves with time. Such problems occur e.g. in surveillance systems for security, in early warning systems of disasters such as earthquakes, hurricanes and forest fires, in collaborative filtering, in search engines for evolving data bases and in reputation systems based on evolving votes. In each of those examples one wants to extract relevant information from an evolving database. Information science is one of the most expansive scientific areas nowadays, much due to the vast amount of information that is available on the Internet, and and the rapid growth of e-business. There are several open problems in these areas of research and even partial answers would have an important impact. There is a pressing need to make progress in analysis tools and in algorithms for such complex tasks. The purpose of the Dagstuhl Seminar 11451 ``Data Mining, Networks and Dynamics'' was to bring together a diverse community of researchers working in different aspects of this exciting field.

Cite as

Lars Elden and Andreas Frommer. Data Mining, Networks and Dynamics (Dagstuhl Seminar 11451). In Dagstuhl Reports, Volume 1, Issue 11, pp. 23-38, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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  author =	{Elden, Lars and Frommer, Andreas},
  title =	{{Data Mining, Networks and Dynamics (Dagstuhl Seminar 11451)}},
  pages =	{23--38},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2012},
  volume =	{1},
  number =	{11},
  editor =	{Elden, Lars and Frommer, Andreas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-33765},
  doi =		{10.4230/DagRep.1.11.23},
  annote =	{Keywords: dynamic networks, data mining, optimization on manifolds, iterative methods, graph algorithms, network models in applications}
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