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ALLSTAT  September 2010

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Subject:

ICDM '10 Top-10 Case Studies: Call, Letters & Criteria

From:

ICDM 2010 <[log in to unmask]>

Reply-To:

ICDM 2010 <[log in to unmask]>

Date:

Sat, 18 Sep 2010 17:57:53 +1000

Content-Type:

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Call for Case Studies (
http://datamining.it.uts.edu.au/icdm10/index.php/call-for/call-for-case-studies
)

ICDM '10: The 10th IEEE International Conference on Data Mining (
http://datamining.it.uts.edu.au/icdm10/)
***************************************************************



Motivation
***************************************************************


Following the successes of the 10 Challenging Problems in Data Mining
Research at ICDMí05
(http://www.cs.uvm.edu/%7Eicdm/10Problems/index.shtml) and the Top 10
Algorithms in Data
Mining at ICDM '06 (http://www.cs.uvm.edu/%7Eicdm/algorithms/index.shtml)
and as part of
the 10 year celebration of IEEEís International Conference on Data Mining
series (ICDM),
the Top-10 Data Mining Case Studies panel at ICDMí10 will present the top 10
data mining
case studies submissions by ten of the top data miners in the field.


The Panel
***************************************************************

The panel's objective is to highlight data mining implementations that have
made a significant
impact in order to help the community to set a baseline for the success
criteria of a successful
contemporary data mining application that practitioners can use to improve
their deployments,
and for data mining researchers to push the state of the art. The moderated
panel will take place
on December 17th at the 10th IEEE International Conference on Data Mining
(ICDMí10).



Topics
***************************************************************

Most operational industrial and scientific systems that involve data mining
to some extent are
likely to be acceptable. Systems that are responsible for mission critical
systems, medical
applications, cash flow, or applications that significantly benefit humanity
will be particularly
good candidates. Other known topic areas of successful data mining
applications include:

- Genomics

- Inventory control

- Customer Relationship Management (CRM)

- ShopBots

- Recommendation systems

- Auction trading systems

- Clinical patient monitoring

- Seismic Data interpretation

- Survival analysis for medical procedures

- Climate analysis

- Correlates of genes with disease

- Dangerous Drug interactions

- Law enforcement applications

- Search Engine Marketing

- Food spoilage elimination

- Price optimization

- Data visualization in mission-critical user interfaces

- Text understanding


Submission instructions
***************************************************************

Please complete the data mining case study questionnaire found here
(
http://www.gabormelli.com/Projects/ICDM-2010_Panel/ICDM10_Panel_Questionnaire.doc)
and submit
it to the panel submission site found here (
http://www.easychair.org/conferences/?conf=icdm10panel)
by the submission deadline date.

You may contact the co-chairs at: [log in to unmask]


Important Dates
***************************************************************

Submissions site open Sept 13, 2010

Submissions site closed Oct. 17, 2010

Notification of selection Nov. 17, 2010

Panel held Dec. 17, 2010



Guidelines
***************************************************************

   1. Advertisement: Data Mining Case Studies is not a sales venue.
References to commercial
products will be carefully scrutinized by our selection committee for
applicability. Where
possible the underlying techniques should be described.
   2. Verifiability: Valid contact information for the company that deployed
the data mining
system must be supplied to the Program Committee. The Program Committee
should be afforded the
right to contact individuals that were the beneficiaries of the data mining
system and ask them
questions about the implementation
   3. Confidentiality: The reviewing process will be confidential.



Venue
***************************************************************

10th IEEE International Conference on Data Mining (ICDM), Sydney, Australia,
Dec. 14thń17th.



Organizing Committee
***************************************************************

    * Gabor Melli (co-chair), PredictionWorks, Canada
    * Xindong Wu (co-chair), University of Vermont, USA
    * Paul Beinat, Neuronworks, Australia
    * Michael Berthold, KNIME, Germany.
    * Longbing Cao, University of Technology Sydney, Australia
    * Christos Faloutsos, Carnegie Mellon University, USA
    * Rayid Ghani, Accenture, USA.
    * Bart Goethals, University of Antwerp, Belgium.
    * Brendan Kitts, Lucid Commerce, USA.
    * Geoff McLachlan, University of Queensland, Australia
    * Jian Pei, Simon Fraser University, Canada.
    * Ashok Srivasta, NASA, USA

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