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MultiClust 2012 : 3rd MultiClust Workshop: Discovering, Summarizing and Using Multiple Clusterings at SDM 2012


When Apr 26, 2012 - Apr 28, 2012
Where Anaheim, California, USA
Submission Deadline Jan 25, 2012
Notification Due Feb 7, 2012
Final Version Due Feb 14, 2012
Categories    machine learning   data mining   clustering

Call For Papers

CFP 3rd MultiClust Workshop
on Discovering, Summarizing and Using Multiple Clusterings
in conjunction with SIAM International Conference on Data Mining, Anaheim, California, USA, 26-28 April 2012.

MultiClust 2012
3rd Workshop on Discovering, Summarizing and Using Multiple Clusterings
will be held in conjunction with SDM 2012
26-28 April 2012, Anaheim, California, USA

Following the success of last MultiClust workshops at KDD 2010 and ECML PKDD 2011, we invite submissions to
the 3rd MultiClust workshop on discovering, summarizing and using multiple clusterings to be held in
conjunction with SDM 2012.

Traditionally, clustering has focused on discovering a single summary of the data. In today's
applications, however, data is collected for multiple analysis tasks. Several features or
measurements provide complex and high dimensional information. In such data, one typically observes
several valid groupings, i.e. each data object fits in different roles. In contrast to traditional
clustering these alternative clusterings describe multiple aspects that characterize the data in
different ways.

The topic of multiple clustering solutions by itself shows multiple research aspects: multiple
alternative solutions vs. a single consensus that integrates different views; given views in
multi-source clustering vs. detection of novel views by feature selection and space transformation
techniques; a virtually unlimited number of alternative solutions vs. a non-redundant output
restricted to a small number of disparate clusterings. Further aspects are induced by data
representations ranging from traditional continuous valued vector spaces to complex models using
graphs, sequences, streams, etc.

The topic of multiple clustering solutions has opened novel challenges in a number of research fields.
Examples from the machine learning and knowledge discovery communities include frequent itemset
mining, ensemble mining, constraint-based mining, theory on summarization of results, or consensus
mining to name only a few. We observe fruitful input from these established related areas. Overall, this
cross-disciplinary research endeavor has recently received significant attention from multiple
communities. In this workshop, we plan to bring together the researchers from the above research areas to
discuss issues in multiple clustering discovery.

The panel discussions at the last MultiClust workshops and a recent tutorial on discovering multiple
clustering solutions document the research interest on this exciting topic. A non-exhaustive list of
topics of interest is given below:

* Discovering multiple clustering solutions
o Alternative clusters / disparate clusters / orthogonal clusters
o Multi-view clustering / subspace clustering / co-clustering
o Multi-source clustering / clustering in parallel universes / multi-represented clustering
o Feature selection and space transformation techniques
o Constraint-based mining for the detection of alternatives
o Non-redundant view detection and non-redundant cluster detection
o Model selection problem: how many clusterings / how many clusters
o Iterative vs. simultaneous processing of multiple views
o Scalability to large and high dimensional databases
o Tackling complex databases (e.g. graphs, sequences, or streams)
* Summarizing multiple clustering solutions
o Ensemble techniques
o Meta clustering
o Consensus mining
o Summarization and compression theory
* Using and evaluating multiple clustering solutions
o Classification based on multiple clusterings
o Evaluation metrics / evaluation methodology for multiple clustering solutions
o Visualization and exploration of multiple clusterings
* Related research fields
o Frequent itemset mining
o Subgroup mining
o Subspace learning
o Multilabel classification
o Relational data mining
o Transfer mining
* Applications of multiple clustering solutions
o Bioinformatics: gene expression analysis / proteomics / ...
o Sensor network analysis
o Social network analysis
o Health surveillance
o Customer segmentation
o ... and many more ...

We encourage submissions describing innovative work in other, related, fields that address the issue of
multiplicity in data mining.

We invite submission of unpublished original research papers that are not under review elsewhere. All
papers will be peer reviewed. Papers may be up to 8 pages long. We also invite vision papers and
descriptions of work-in-progress or case studies on benchmark data as short paper submissions of up to 4
pages. If accepted, at least one of the authors must attend the workshop to present the work.

Contributions should be submitted in pdf format using the workshop’s EasyChair submission site at The submitted papers must be written
in English and formatted according to the SDM 2012 submission guidelines. We would like to encourage you
to prepare your paper in LaTeX2e. Papers should be formatted using the SIAM SODA macro, which is available
through the SIAM website. You can access it at The
filename is soda2e.all. Make sure you use the macros for SODA and Data Mining Proceedings; papers
prepared using other proceedings macros will not be accepted.

If you are considering submitting to the workshop and have questions regarding the workshop scope or need
further information, please do not hesitate to contact the PC chairs.

We will edit on-line proceedings of all accepted papers so that the results are widely accessible.
Proceedings will be published through the CEUR Workshop Proceedings ( publication
service in time for the workshop. If there is sufficient interest and quality of papers, we will also
consider a post-workshop publication (e.g., as a special issue in a journal).

Submission deadline: (EXTENDED) Jan 25, 2012
Acceptance notification: Feb 7, 2012
Camera-ready deadline: Feb 14, 2012

Emmanuel Müller, Karlsruhe Institute of Technology, Germany
Thomas Seidl, RWTH Aachen University, Germany
Suresh Venkatasubramanian, University of Utah, USA
Arthur Zimek, LMU Munich, Germany

Ira Assent (Aarhus University, Denmark)
James Bailey (University of Melbourne, Australia)
Carlotta Domeniconi (George Mason University, USA)
Xiaoli Fern (Oregon State University, USA)
Shahriar Hossain (Virginia Tech, USA)
Michael Houle (National Institute of Informatics, Japan)
Daniel Keim (University of Konstanz, Germany)
Themis Palpanas (University of Trento, Italy)
Jörg Sander (University of Alberta, Canada)
Alexander Topchy (Nielsen Media Research)
Jilles Vreeken (University of Antwerp, Belgium)

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