marami

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marami@lipn.univ-paris13.fr

May 2014

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[CFP: Special Session: Multiplex Network Mining - New Deadline : 31 May 2014]
by rushed Kanawati 15 May '14

15 May '14

** thanks to distribute this call for papers, with apologizes in case of multiple reception ** _______________________________________________________________________ CFP: Special session on Multiplex Network Mining@CASoN?2014 30 July, 1 August 2014, Porto Portugal Abstract submission deadline : 20 MAY 2014 Submission deadline (extended) : 31 May 2014 web site : http://lipn.fr/mnm14 submission site : https://www.easychair.org/conferences/?conf=cason2014 ____________________________________________________________________________ Context Complex networks used to model interactions in real-world phenomena are often heterogeneous network with d ifferent types of nodes and edges. Focusing on a single type of nodes, a complex network would be better described by a multiplex: a set of nodes related to each other with different types of relations. This representation is much richer than simple complex networks often used to model complex interaction systems. However, this poses the challenge to provide adequate answers to all basic network analysis tasks that have been studied and provided in the recent few years for the case of homogeneous networks. This include for instance: the problem of node ranking (computing nodes centralities), community detection, link prediction, information diffusion models and network visualization. Almost all work in the field of multiplex network analysis are based on transforming the problem, in a way or another to the classical case of homogeneous network analysis. Existing approaches include: layer aggregation based approaches or applying ensemble methods on results obtained on eac h layer aside . Little work has focused on analyzing all layers at once. The goal of this session is to make the point on new approaches for multiplex network analysis and mining. Topics A non-exhaustive list of relevant topics include: Models & measures for multiplex networks Centrality in multiplex networks Paths, clustering coefficient in multiplex networks Random walks on multiplex networks Co-evolution of layers in multiplex networks. Layer aggregation approaches. Vertex similarity in multiplex network Community detection in multiplex network Multiplex network partitioning Multi-layer modularity functions Overlapping community detection Dynamic & multiplex networks Link prediction in multiplex network Missing links detection Multiplex network evolution models Dynamic networks as a multiplex Machine learning approaches Ensemble learning for multiplex network mining Multi-view clustering Collaboratif learning Applications Recommender systems Heterogeneous network mining Reality mining Mobility data mining Networks of networks analysis Submitted papers should be original and contain contributions of theoretical, experimental or application nature, or be unique experience reports. The page limit for a full-length paper is 6 pages. Short papers describing novel research visions, work-in-progress or less mature results are also welcome, with a minimum limit of 4 pages. All submissions should be in the IEEE 8.5 two-column format. Papers will be evaluated for originality, significance, clarity, and soundness, and will be reviewed by at least three independent reviewers. The conference proceedings will be distributed amongst the participants during the conference. Accepted papers must be presented by author(s) personally to be published in the conference proceedings. Program Committee Marc Barthelemy, CEA-IPhT, CNRS URA 2306 Michele Coscia, Cen ter for International Development - Harvard University Manlio De Domenico, Universitat Rovira i Virgili Jean-loup Guillaume, LIP6, UMPC, Paris, France Rushed Kanawati (chair), Sorbonne Paris Cité, LIPN CNRS UMR 7030 Renaud Lambiotte, University of Namur Christine Largeron, LHC, Univ. St.Etienne Maria Malek, LARIS, EISTI Cergy Metteo Magnani, Uppsala University Ruggero Pensa, University of Torino Céline Rouveirol, Sorbonne Paris cité, LIPN CNRS UMR 7030 Sun Yizhou, Northeastern University _______________________________________ Rushed Kanawati, PhD Associate professor in Computer Science LIPN CNRS UMR 7030 Institut Galilée - Université Paris Nord 99 AV. J.B. Clément 93430 Villetaneuse - France www-lipn.univ-paris13.fr/~kanawati

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