Data Mining in various forms is becoming a major component of how businesses operate. Almost every business process today involves some form of data mining. Customer Relationship Management, Supply Chain Optimization, Demand Forecasting, Assortment Optimization, and Business Intelligence are just some examples of business functions that haven been impacted by data mining techniques.

Even though data mining has become critical to businesses, most of the academic research in data mining is conducted on mostly publicly available data sources. This is mainly due to two reasons: 1) the unavailability of large, new, and interesting sources of data to academic researchers. 2) limited access to domain experts who can provide a practical perspective on existing problems and provide a new set of research problems. Corporations are typically wary of releasing their internal data to academic and in most cases, there is limited interaction between industry practitioners and academic researchers working on related problems in similar domains.

The goals of this workshop are:

1. Bring together researchers (from both academia and industry) as well as practitioners from different fields to talk about their different perspectives and to share their latest problems and ideas.

2. Attract business professionals who have access to interesting sources of data and business problems but not the expertise in data mining to solve them effectively.

We would like to focus on the following topics in the workshop:

• fielded applications of data mining
• new classes of research problems motivated by real-world business problems.
• data mining applications as components of business processes
• how to sell data mining technology/projects inside your organization or to your customers
• integration of data mining technologies with other kind of technologies
• lessons learned from practical experiences

Submissions                                                                                 

Submissions should be sent by June 10, 2006, in electronic form as a PDF (or Word) file, to rayid.ghani@accenture.com..

Submissions are limited to a maximum of 4 pages. Submitted papers will be reviewed by referees from the Program Committee. Accepted papers will be published in the Workshop proceedings.

Notification of acceptance and rejection will be sent by July 5, 2006.

Submission Deadline: June 10, 2006
Acceptance Notification: July 5, 2006
Camera-ready Copies: July 15, 2005
Workshop date: August 20, 2006
 

Schedule                                                                                                 

Complete Workshop Proceedings (NEW)

Panel Discussion:  Bridging the Gap between Data Mining Research and Practical Business Applications

Panel Discussion: Deploying Data Mining Solutions: Stories, Challenges, and Open Issues

Accepted Papers:

• Discovering Telecom Fraud Situations through Mining Anomalous Behavior Patterns by Ronnie Alves, Pedro Ferreira, Orlando Belo, Joao Lopes, Joel Ribeiro, Luís Cortesão

• Interactivity Closes the Gap: Lessons Learned in an Automotive Industry Application by Axel Blumenstock, Jochen Hipp, Carsten Lanquillon, Rudiger Wirth

• The Business Practitioner’s Viewpoint-Discovering and Resolving Real-Life Business Concerns through the Data Mining Exercise by Richard Boire

• Customer Validation of Commercial Predictive Models by Tilmann Bruckhaus, William Guthrie

• A boosting approach for automated trading by Germán Creamer, Yoav Freund

• Zen and the Art of Data Mining by T. Dasu, E. Koutsofios, J. Wright

• Data mining in the real world: What do we need and what do we have? by Françoise Soulié Fogelman

• Forecasting Online Auctions using Dynamic Models by Wolfgang Jank, Galit Shmueli, Shanshan Wang

• Business Event Advisor: Mining the Net for Business Insight with Semantic Models, Lightweight NLP, and Conceptual Inference by Alex Kass, Christopher Cowell-Shah

• Mining and Querying Business Process Logs by Akhil Kumar

• Driving High Performance for a Large Wireless Communications Company through Advanced Customer Insight by Ramin Mikaili, Lynette Lilly

• Quantile Trees for Marketing by Claudia Perlich, Saharon Rosset

• A Decision Management Approach to Basel II Compliant Credit Risk Management by Peter van der Putten, Arnold Koudijs, Rob Walker

• Resolving the Inherent Conflicts of Value Definition in Academic-Industrial Collaboration by David Selinger, Tyler Kohn

• Using Data Mining in Procurement Business Transformation Outsourcing by Moninder Singh, Jayant R. Kalagnanam

Workshop Chairs                                                                                  

Rayid Ghani
Accenture Technology Labs, 161 N. Clark St., Chicago, IL 60601
rayid.ghani@accenture.com

Carlos Soares
LIACC/Faculty of Economics, University of Porto
csoares@liacc.up.pt

Program Committee                                                                               

Chid Apte, IBM Research
Paul Bradley, Apollo Data Technologies
Pavel Brazdil, University of Porto
Doug Bryan, KXEN
Raul Domingos, SPSS
Robert Engels, CognIT
Andrew Fano, Accenture Technology Labs
Usama Fayyad, Yahoo
Ronen Feldman, Clearforest
Marko Grobelnik, Jozef Stefan Institute
Robert Grossman, Open Data Partners and University of Illinois at Chicago
Alípio Jorge, University of Porto
Tom Khabaza, SPSS
Jörg-Uwe Kietz, Kdlabs AG
Arno Knobbe, Kiminkii/University of Utrecht
Dragos Margineantu, Boeing Company
Gabor Melli, PredictionWorks
Natasa Milic-Frayling, Microsoft Research
Dunja Mladenic, Jozef Stefan Institute
Gregory Piatetsky-Shapiro, KDNuggets
Katharina Probst, Accenture Technology Labs
Foster Provost, New York University
Peter van der Putten, Chordiant Software
Galit Shmueli, University of Maryland
Gary Weiss, Fordham University
Luís Torgo, University of Porto
Alexander Tuzhilin, New York University
Dave Watkins, SPSS