Call for Papers

Eleventh Workshop on Mining and Learning with Graphs

August 11, 2013 - Chicago, IL
(co-located with KDD 2013)

This workshop is a forum for exchanging ideas and methods for mining and learning with graphs, developing new common understandings of the problems at hand, sharing of data sets where applicable, and leveraging existing knowledge from different disciplines. The goal is to bring together researchers from academia, industry, and government, to create a forum for discussing recent advances graph analysis. In doing so we aim to better understand the overarching principles and the limitations of our current methods, and to inspire research on new algorithms and techniques for mining and learning with graphs.

To reflect the broad scope of work on mining and learning with graphs, we encourage submissions that span the spectrum from theoretical analysis, to algorithms and implementation, to applications and empirical studies. In terms of application areas, the growth of user-generated content on blogs, microblogs, discussion forums, product reviews, etc., has given rise to a host of new opportunities for graph mining in the analysis of social media. Social media analytics is a fertile ground for research at the intersection of mining graphs and text. As such, this year we especially encourage submissions on theory, methods, and applications focusing on the analysis of social media.

Topics of interest include, but are not limited to:

Theoretical aspects:
Computational or statistical learning theory related to graphs
Theoretical analysis of graph algorithms or models
Sampling and evaluation issues in graph algorithms
Relationships between MLG and statistical relational learning or inductive logic programming

Algorithms and methods:
Graph mining
Kernel methods for structured data
Probabilistic and graphical models for structured data
(Multi-) Relational data mining
Methods for structured outputs
Statistical models of graph structure
Combinatorial graph methods
Spectral graph methods
Semi-supervised learning, active learning, transductive inference, and transfer learning in the context of graph

Applications and analysis:
Analysis of social media
Social network analysis
Analysis of biological networks
Large-scale analysis and modeling

We invite the submission of regular research papers (6-8 pages) as well as position papers (2-4 pages). Authors whose papers are accepted to the workshop will have the opportunity to participate in a poster session, and some set may also be chosen for oral presentation.

Key Dates

Paper submission - June 6, 2013

Author notification - June 25, 2013

MLG 2013 Workshop - Aug 11, 2013