<div dir="ltr"><div>Eleventh Workshop on Mining and Learning with Graphs (<span class="">MLG</span> 2013)</div><div>August 11, 2013 - Chicago, IL (co-located with KDD 2013)</div><div><a href="http://snap.stanford.edu/mlg2013/" target="_blank">http://snap.stanford.edu/mlg2013/</a></div>
<div>Submission Deadline: June 6, 2013</div><div><br></div><div>This workshop is a forum for exchanging ideas and methods for mining and</div><div>learning with graphs, developing new common understandings of the problems at</div>
<div>hand, sharing of data sets where applicable, and leveraging existing knowledge</div><div>from different disciplines. The goal is to bring together researchers from</div><div>academia, industry, and government, to create a forum for discussing recent</div>
<div>advances graph analysis. In doing so we aim to better understand the overarching</div><div>principles and the limitations of our current methods, and to inspire research</div><div>on new algorithms and techniques for mining and learning with graphs.</div>
<div><br></div><div>To reflect the broad scope of work on mining and learning with graphs, we</div><div>encourage submissions that span the spectrum from theoretical analysis, to</div><div>algorithms and implementation, to applications and empirical studies. In terms</div>
<div>of application areas, the growth of user-generated content on blogs, microblogs,</div><div>discussion forums, product reviews, etc., has given rise to a host of new</div><div>opportunities for graph mining in the analysis of social media. Social media</div>
<div>analytics is a fertile ground for research at the intersection of mining graphs</div><div>and text. As such, this year we especially encourage submissions on theory,</div><div>methods, and applications focusing on the analysis of social media.</div>
<div><br></div><div>Topics of interest include, but are not limited to:</div><div><br></div><div>Theoretical aspects:</div><div>* Computational or statistical learning theory related to graphs</div><div>* Theoretical analysis of graph algorithms or models</div>
<div>* Sampling and evaluation issues in graph algorithms</div><div>* Analysis of dynamic graphs</div><div>* Relationships between <span class="">MLG</span> and statistical relational learning or inductive</div><div>logic programming</div>
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<br></div><div>Algorithms and methods:</div><div>* Graph mining</div><div>* Kernel methods for structured data</div><div>* Probabilistic and graphical models for structured data</div><div>* (Multi-) Relational data mining</div>
<div>* Methods for structured outputs</div><div>* Statistical models of graph structure</div><div>* Combinatorial graph methods</div><div>* Spectral graph methods</div><div>* Semi-supervised learning, active learning, transductive inference, and</div>
<div>transfer learning in the context of graph</div><div><br></div><div>Applications and analysis:</div><div>* Analysis of social media</div><div>* Social network analysis</div><div>* Analysis of biological networks</div>
<div>* Knowledge graph construction</div><div>* Large-scale analysis and modeling</div><div><br></div><div>We invite the submission of regular research papers (6-8 pages) as well as</div><div>position papers (2-4 pages). Authors whose papers are accepted to the workshop</div>
<div>will have the opportunity to participate in a poster session, and some</div><div>set may also be chosen for oral presentation.</div><div><br></div><div>Timeline:</div><div>Submission Deadline: June 6</div><div>Notification: June 25</div>
<div>Final Version: July 6</div><div>Workshop: August 11</div><div><br></div><div>Submission instructions can be found on</div><div><a href="http://snap.stanford.edu/mlg2013/instructions.html" target="_blank">http://snap.stanford.edu/mlg2013/instructions.html</a></div>
<div><br></div><div>Please send enquires to <a href="mailto:jmcauley@cs.stanford.edu" target="_blank">jmcauley@cs.stanford.edu</a></div><div><br></div><div>We look forward to seeing you at the workshop!</div><div><br></div>
<div>Lada Adamic, Lise Getoor, Bert Huang, Jure Leskovec, Julian McAuley (chairs)</div>
<div><br></div>Edoardo Airoldi, Leman Akoglu, Aris Anagnostopoulos, Arindam Banerjee, Christian Bauckhage, Francesco Bonchi, Ulf Brefeld, Tina Eliassi-Rad, Thomas Gaerner, Brian Gallagher, David Gleich, Marco Gori, Mohammad Hasan, Jake Hofman, Jiawei Han, Larry Holder, Manfred Jaeger, Tamara Kolda, U Kang, Kristian Kersting, Kristina Lerman, Bo Long, Sofus Macskassy, Thorsten Meinl, Prem Melville, Dunja Mladenic, Jennifer Neville, Srinivasan Parthasarathy, Jan Ramon, Bing Tian Dai, Hanghang Tong, Chris Volinsky, Stefan Wrobel, Xifeng Yan, Xintian Yang, Philip Yu, Mohammed Zaki, Liang Zhang, Mark Zhang (program committee)<br>
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