Call for papers: MLG-2012 (Tenth workshop on Mining and Learning with Graphs)

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               MLG-2012: Call for papers
Tenth workshop on Mining and Learning with Graphs (MLG-2012).
http://dtai.cs.kuleuven.be/events/mlg2012/

               Edinburg, July 1st, 2012
               Co-located with ICML-2012
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*Introduction:*
There is a great deal of interest in analyzing data that is best
represented as a graph. Examples include the WWW, social networks,
biological networks, communication networks, food webs, and many others.
The importance of being able to effectively mine and learn from such data
is growing, as more and more structured and semi-structured data is
becoming available. Traditionally, a number of subareas have worked with
mining and learning from graph structured data, including communities in
graph mining, learning from structured data, statistical relational
learning, inductive logic programming, and, moving beyond subdisciplines in
computer science, social network analysis, and, more broadly network
science. The objective of this workshop is to bring together researchers
from a variety of these areas, and discuss commonality and differences in
challenges faced, survey some of the different approaches, and provide a
forum for to present and learn about some of the most cutting edge research
in this area. As an outcome, we expect participants to walk away with a
better sense of the variety of different tools available for graph mining
and learning, and an appreciation for some of the interesting emerging
applications for mining and learning from graphs.

The goal of this workshop will be to structure and explore the
state-of-the-art algorithms and methods, to examine graph-based models in
the context of real-world applications, and to identify future challenges
and issues. In particular we are interested in the following topics:
* Relationships between mining and learning with graphs and statistical
relational learning
* Relationships between mining and learning with graphs and inductive logic
programming
* Relationships between mining and learning with graphs and algorithmic
graph theory and related fields
* Kernel methods for structured data
* Probabilistic models for structured data
* Graph mining
* (Multi-)relational data mining
* Methods for structured outputs
* Network analysis
* Large-scale learning and applications
* Sampling issues in graph algorithms
* Evaluation of graph algorithms
* Graph mining benchmarks and datasets
* Applications of graph mining in real world domain

*Submission Guildance:*
We invite both full papers presenting new contributions and short papers
describing work in progress or open problems.  Full papers should be at
most 8 pages (ICML format), short papers and open problem statements at
most 3 pages.

Papers can be submitted online via
https://www.easychair.org/account/signin.cgi?timeout=1;conf=mlg2012

Authors whose papers were accepted to the workshop will have the
opportunity to give a short presentation at the workshop as well as present
their work in a poster session.


*Important dates:*
Paper submission deadline    May 7th
Notification of acceptance   May 21th
Final paper submission       June 18th
Workshop                     July 1st


*Organizers:*
Jan Ramon
Hanghang Tong