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

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Category MULTICLUST 2012

Deadline: January 13, 2012 | Date: April 26, 2012-April 28, 2012

Venue/Country: California, U.S.A

Updated: 2011-11-12 20:55:21 (GMT+9)

Call For Papers - CFP

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=multiclust2012 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)