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CS8803-NS Network Science Fall 2013

CS8803-NS Network Science Fall 2013. Instructor: Constantine Dovrolis constantine@gatech.edu http://www.cc.gatech.edu/~dovrolis/Courses/NetSci/. Disclaimers.

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CS8803-NS Network Science Fall 2013

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  1. CS8803-NSNetwork ScienceFall 2013 Instructor: Constantine Dovrolis constantine@gatech.edu http://www.cc.gatech.edu/~dovrolis/Courses/NetSci/

  2. Disclaimers The following slides include only the figures or videos that we use in class; they do not include detailed explanations, derivations or descriptionscovered in class. Many of the following figures are copied from open sources at the Web. I do not claim any intellectual property for the following material.

  3. Outline • Variations of the community detection problem • Weighted and/or directed networks • Overlapping communities • Dynamic communities • Community detection based on info theory • Properties of real-world network communities • Applications of community detection • In social networks • In biological networks • In brain networks • In climate networks

  4. In addition to its application domain, this paper covers: • Modularity maximization using Simulated Annealing • Classification of nodes (“the role of each node”) based on its connectivity within a community and across communities • Within-module degree • Participation coefficient • Which nodes are more conserved by evolution?

  5. http://memshub.org/resources/200/watch?resid=201

  6. Modularity for weighted, directed networks

  7. http://www.cise.ufl.edu/~tdinh/

  8. http://www.nature.com/nature/journal/v446/n7136/fig_tab/nature05670_F1.htmlhttp://www.nature.com/nature/journal/v446/n7136/fig_tab/nature05670_F1.html

  9. Ground-truth in network communities?

  10. Power method: How to compute the fraction of time spent at each node by a “random walker”?(suppose the network is undirected, for now) http://www.biomedcentral.com/1471-2105/7/71/figure/F8?highres=y

  11. Huffman encoding

  12. For directed networks:

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