.. image:: pyeco.png
    :height: 20
    :alt: Economie
    :target: http://www.xavierdupre.fr/app/ensae_teaching_cs/helpsphinx/td_2a_notions.html#pour-un-profil-plutot-economiste

.. image:: pystat.png
    :height: 20
    :alt: Statistique
    :target: http://www.xavierdupre.fr/app/ensae_teaching_cs/helpsphinx/td_2a_notions.html#pour-un-profil-plutot-data-scientist

.. _l-ml2a-communities:

Communautés
+++++++++++

Déterminer les communautés est un problème assez semblable au problème
de clustering mais on cherche aussi à en déterminer le centre ou encore
à catégoriser chaque individu autrement que par son appartenance à un cluster.

*(à venir)*

*Lectures*

* `Katz centrality <https://en.wikipedia.org/wiki/Katz_centrality>`_
* `Fast unfolding of communities in large networks <https://arxiv.org/pdf/0803.0476v2.pdf>`_ (Louvain)
* `Modularity and community structure in networks <https://arxiv.org/abs/physics/0602124>`_
* `Computing communities in large networks using random walks (long version) <https://arxiv.org/abs/physics/0512106>`_
* `Finding and evaluating community structure in networks <https://arxiv.org/abs/cond-mat/0308217>`_
* `Mixing patterns in networks <http://www.leonidzhukov.net/hse/2015/sna/papers/mixing_patterns.pdf>`_
* `Networks in Their Surrounding Contexts <https://www.cs.cornell.edu/home/kleinber/networks-book/networks-book-ch04.pdf>`_
* `Local Network Community Detection with Continuous Optimization of Conductance and Weighted Kernel K-Means <http://jmlr.org/papers/volume17/16-043/16-043.pdf>`_
* `Learning Communities in the Presence of Errors <http://www.jmlr.org/proceedings/papers/v49/makarychev16.pdf>`_
* `Fast Detection of Community Structures using Graph Traversal in Social Networks <https://arxiv.org/pdf/1707.04459.pdf>`_
* `Community Extraction in Multilayer Networks with Heterogeneous Community Structure <http://www.jmlr.org/papers/volume18/16-645/16-645.pdf>`_
* `Discovering the hidden community structure of public transportation networks <https://arxiv.org/pdf/1801.03857.pdf>`_
  (article plutôt didactique)
* `Python implementation of Newman's spectral methods to maximize modularity <https://github.com/zhiyzuo/python-modularity-maximization>`_

*Modules*

* `python-louvain <https://github.com/taynaud/python-louvain>`_
* `GraKeL <https://github.com/ysig/GraKeL>`_ :
  algorithmes sur les graphes, plus court chemin,
  marches aléatoires, méthodes à noyaux
* `scikit-network <https://scikit-network.readthedocs.io/en/latest/index.html>`_ :
  de nombreux algorithmes comme PageRank, Louvain, ...