Connectionists: [CFP] KDD MLG'23 -- 19th International Workshop on Mining and Learning with Graphs

[Shobeir Fakhraei]

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19th International Workshop on Mining and Learning with Graphs (KDD-MLG
2023)

August, 2023

In conjunction with KDD

http://www.mlgworkshop.org/2023

Submission Deadline: May 30, 2023

Call for papers:

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 in 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, empirical studies and
reflection papers. As an example, 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. More recently, the advent of neural methods for learning graph
representations has spurred numerous works in embedding network entities
for diverse applications including ranking and retrieval, traffic routing
and drug-discovery.  We encourage submissions on theory, methods, and
applications focusing on a broad range of graph-based approaches in various
domains.

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
      -

      Analysis of dynamic graphs
      -

   Algorithms and methods:
   -

      Graph mining
      -

      Probabilistic and graphical models for structured data
      -

      Heterogeneous/multi-model graph analysis
      -

      Network embedding and graph neural network models
      -

      Statistical models of graph structure
      -

      Combinatorial graph methods
      -

      Semi-supervised learning, active learning, transductive inference,
      and transfer learning in the context of graphs
      -

   Applications and analysis:
   -

      Analysis of social media
      -

      Analysis of biological networks
      -

      Knowledge graph construction
      -

      Large-scale analysis and modeling

We welcome many kinds of papers, such as, but not limited to:

   -

   Novel research papers
   -

   Demo papers
   -

   Work-in-progress papers
   -

   Visionary papers (white papers)
   -

   Appraisal papers of existing methods and tools (e.g., lessons learned)
   -

   Evaluatory papers which revisit validity of domain assumptions
   -

   Relevant work that has been previously published
   -

   Work that will be presented at the main conference


Authors should clearly indicate in their abstracts the kinds of submissions
that the papers belong to, to help reviewers better understand their
contributions. Submissions must be in PDF, no more than 8 pages long
(excluding references)— shorter papers are welcome — and formatted
according to the standard double-column ACM Proceedings Style
<http://www.acm.org/publications/proceedings-template#aL2>. The accepted
papers will be published on the workshop’s website and will not be
considered archival for resubmission purposes. Authors whose papers are
accepted to the workshop will have the opportunity to participate in a
spotlight and poster session, and a subset will also be chosen for oral
presentation.

Timeline:

Submission Deadline: May 30, 2023

Notification: June 23, 2023

Final Version: July 10, 2023

Workshop: August TBD, 2023

Submission instructions can be found on http://www.mlgworkshop.org/2023/

Please send enquiries to chair at mlgworkshop.org

Organizers:

Neil Shah (Snap)

Shobeir Fakhraei (Amazon)

Da Zheng (Amazon)

Bahare Fatemi (Google)

Leman Akoglu (CMU)

To receive updates about the current and future workshops and the Graph
Mining community, please join the mailing list:
https://groups.google.com/d/forum/mlg-list

or follow the twitter account: https://twitter.com/mlgworkshop
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