DMCS 2011 - The Fourth Workshop on Data Mining Case Studies

From its inception the field of data mining has been guided by the need to solve practical problems. Yet a cursory examination of the publications shows that few papers describe a completed implementation or what we will term a “case study”. The small number of case studies is counter-balanced by their prominence. Anecdotally case studies are one of the most discussed topics at data mining conferences. Some of the benefits of good case studies include

1. Inspiration: Case studies provide examples that can inspire data mining researchers to pursue important new technical directions.
2. Innovation: Data mining case studies demonstrate how whole problems were solved - not just part of the problem. Often building the prediction algorithm is only 10% of the problem - the other aspects that comprise a successful deployment are valuable for practitioners to understand.
3. Education: People are more likely to remember stories than facts.
4. Media Coverage: The media is more likely to report on completed data mining applications, than they are on isolated algorithms. We have an opportunity to present positive success stories to the wider community.
5. Public relations: Applications, particularly those that are socially beneficial, will help our perception both within the wider public and other scientific fields.
6. Connections to Other Scientific Fields: Completed systems knit together a range of scientific and engineering disciplines such as signal processing, chemistry, optimization theory, auction theory and so on. Fostering meaningful connections to these fields will benefit data mining academically, and will assist data mining practitioners to learn how to harness these fields to develop successful applications.

The Workshop

The Data Mining Case Studies Workshop and Practice Prize was established in 2005 showcase the very best in data mining case deployments. Data Mining Case Studies continues into its third year, to be held at ICDM-2011. Data Mining Case Studies will highlight data mining implementations that have been responsible for a significant and measurable improvement in business operations, or an equally important scientific discovery, or some other benefit to humanity.

Examples of Data Mining Case Studies from previous years have included: (a) a medical application that has save hundreds of lives by mining through hundreds of thousands of patient records to identify patients who have show all the signs for heart disease, yet have not been prescribed heart medication, (b) a system which has uncovered hundreds of millions in sheltered tax evasion rings, (c) a system which has raised revenue by improved cross-selling of computer peripherals and equipment.

Data Mining Case Studies will allow papers greater latitude in (a) range of topics - authors may touch upon areas such as optimization, operations research, inventory control, and so on, (b) page length - longer submissions are allowed, (c) scope - more complete context, problem and solution descriptions will be encouraged, (d) prior publication - if the paper was published in part elsewhere, it may still be considered if the new article is substantially more detailed, (e) novelty ? the use of established techniques to achieve successful implementations will be given partial allowance.

Unsuccessful data mining systems that describe lessons learned and “war stories” will also be assessed.

The Data Mining Practice Prize

Introduction: The Data Mining Practice Prize will be awarded for the best Data Mining Case Study submission. The prize will be awarded for work that has had a significant and quantitative impact in the application in which it was applied, or has significantly benefited humanity.

Eligibility: All papers submitted to Data Mining Case Studies will be eligible for the Data Mining Practice Prize, with the exception of any persons serving on the Data Mining Practice Prize Committee, in addition to memberes of Sponsoring companies. Eligible authors must consent to allowing the Practice Prize Committee independently validate their claims by contacting third parties and their deployment client for independent verification and analysis.

Award: Winners will receive a variety of honors including:
Prize money comprising $200 .
Plaque.
Awards Dinner with organizers and prize winners.

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. If you are unsure as to the suitability of your paper, please contact the organizers with your topic at the email address at the bottom of the page. Topics include but are not limited to

- 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