Motivation

Following the successes of the 10 Challenging Problems in Data Mining Research at ICDM’05 and the Top 10 Algorithms in Data Mining at ICDM '06 and as part of the 10 year celebration of IEEE’s International Conference on Data Mining series (ICDM), the Top-10 Data Mining Case Studies panel at ICDM’10 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 (ICDM’10).

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) and submit it to the panel submission site found (here) by the submission deadline date.

You may contact the co-chairs at: This e-mail address is being protected from spambots. You need JavaScript enabled to view it .

Important Dates

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. 14^th–17^th.

Organizing Committee

• Gabor Melli (co-chair), PredictionWorks, Canada

• Xindong Wu (co-chair), University of Vermont, USA

• Paul Beinat, Neuronworks, Australia

• 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

• Rong Duan, ATT, USA