| |||||||||||||||
DyNaK 2014 : 2ed International workshop on Dynamic Networks and Knowledge Discovery | |||||||||||||||
Link: http://lipn.univ-paris13.fr/dynak2 | |||||||||||||||
| |||||||||||||||
Call For Papers | |||||||||||||||
Modeling and analyzing networks is a major emerging topic in different research areas, such as computational biology, social science, document retrieval, etc. Nowadays, the scientific communities have access to huge volumes of network-structured data, such as social networks, gene/proteins/metabolic networks, sensor networks, peer-to-peer networks. Most often, these data are not only static, but they are collected at different time points. This dynamic view of the system allows the time component to play a key role in the comprehension of the evolutionary behavior of the network.
Handling such data is a major challenge for current research in machine learning and data mining, and it has led to the development of recent innovative techniques that consider complex/multi-level networks, time-evolving graphs, heterogeneous information (nodes and links), and requires scalable algorithms that are able to manage huge and complex networks. DyNaK workshop is motivated by the interest of providing a meeting point for scientists with different backgrounds that are interested in the study of large complex networks and the dynamic aspects of such networks. It aims at attracting contributions from both aspects of networks analysis: large real network analysis and modeling, and knowledge discovery within those networks. Authors are invited to submit previously unpublished papers on their theortical research and/or applications in any topic related to one or more of the workshop topics. A non exhaustive list of topics is given hereafter: Network inference from raw data -Graphical models -Graph mining algorithms -Graph kernel algorithms -Relational learning algorithms -Matrix/Tensor methods -Information retrieval algorithms -Bayesian method Evolutionary clustering -Mining heterogenous networks -Multiplex network analysis & mining -Bisociative information discovery -Clustering/Co-clustering/Biclustering -Pattern mining with constraints -Community detection -Social & biological networks analogy Applications -Recommender systems -System biology: regulatory gene networks, protein-protein interaction, miRNA networks, metabolic networks -Social networks: folksonomies, digital libraries, information networks, social media, collaborative networks -Sensor networks, peer-to-peer networks, Web, agent networks, body sensor networks We welcome original contributions, either theoretical or empirical, describing ongoing projects or completed work (even partially published). The instructions for authors and the LaTeX packages can be found at http://www.springer.de/comp/lncs/authors.html. Paper length should not exceed 12 pages. Following the first edition of DyNak workshop, a special issue of the International jouranl of Intelligent Data Analysis is now under edition. We expect to do the same for this second edition. To submit your paper(s), please log into the submission website : https://www.easychair.org/conferences/?conf=dynak2 |
|