The Industrial/Government Applications Track of the Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2007) will highlight challenges, lessons, concerns, and research issues arising out of deploying applications of KDD technology. The focus would be on promoting the exchange of ideas between researchers and practitioners of data mining.
The KDD-2007 Industrial/Government Applications (I/G) Track seeks to:
provide a forum for exchanging ideas between KDD practitioners, researchers, companies, and government organizations; and
help commercial and government organizations highlight successful KDD applications,
raise interesting (research) challenges and other concerns more specific to industry and government -- customer privacy issues, analysis of data not generally available in academia, issues of scale that arise more heavily in a corporate setting, etc.
The I/G Applications Track solicits papers describing attempts to deploy KDD solutions relevant to commercial or government challenges. The primary emphasis is on papers that advance our understanding of practical, applied, or pragmatic issues and perhaps highlight new research challenges in real KDD applications. Applications can be in any field including scientific, engineering, commercial, governmental, social, or political. The I/G Applications Track will consist of competitively-selected contributed papers - presented in oral and poster form - as well as invited talks. The full conference will also feature keynote presentations, workshops, tutorials, research track papers, and the KDD Cup competition. We envision submissions along four sub-areas:
Emerging applications, technology, and issues;
Deployed KDD case studies;
Product and experience descriptions; and
Pragmatic issues and research considerations in fielding real applications.
Emerging application, technology, and issue papers discuss prototype applications, tools for focused domains or tasks, useful techniques or methods, useful system architectures, scalability enablers, tool evaluations, or integration of KDD and other technologies. Case studies describe deployed projects with measurable benefits that include KDD technology. Such papers need to demonstrate the importance and impact of the work clearly. Product submissions clearly describe KDD technology embedded in commercial products (without otherwise being a product advertisement). Pragmatic issues and considerations include important practical and research considerations, approaches, and architectures that enable successful applications. Submitters are encouraged (but not required) to select one (or more) of these sub-areas for their papers.In their submission, authors are required to explain why the application is important, the specific need for KDD technology to solve the problem (including why other methods perhaps not based on data mining may fall short), and any innovations or lessons learned in the solution.
For submission details and organizers, see www.kdd2007.com.
Important Dates:
Abstracts due: 23 February, 2007 Paper submissions due: 28 February, 2007 (9 pages)
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