MultiClust 2012 - 3rd Workshop on Discovering, Summarizing and Using Multiple Clusterings

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

http://www.dbs.ifi.lmu.de/research/MultiClust2012/


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.

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

SUBMISSION GUIDELINES
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 http://www.easychair.org/conferences/?conf=multicl... 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 http://www.siam.org/proceedings/macros.php. 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.

PROCEEDINGS
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 (CEUR-WS.org) 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).

IMPORTANT DATES
Submission deadline: Jan 13, 2012
Acceptance notification: Feb 7, 2012
Camera-ready deadline: Feb 14, 2012

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

PROGRAM COMMITTEE (so far)
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)