KDD-09 Second Call for Research Papers

KDD-09 Second Call for Research Papers

Posted by Rebecca Martin on Mon, 26/01/2009 - 01:00

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KDD-2009: The Fifteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'09)

Paris, France
June 28 - July 1, 2009.

http://www.kdd.org/kdd2009/

CALL FOR RESEARCH PAPERS

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The annual ACM SIGKDD conference is the premier international forum for data mining researchers and practitioners from academia, industry, and government to share their ideas, research results and experiences. KDD-09 will feature keynote presentations, oral paper presentations, poster sessions, workshops, tutorials, panels, exhibits, demonstrations, and the KDD Cup competition.

We invite submissions on all aspects of knowledge discovery and data mining.
We especially encourage papers relevant to KDD that cut across disciplines such as machine learning, pattern recognition, statistics, databases, theory, mathematical optimization, data compression, cryptography, and high performance computing. Papers are expected to describe innovative ideas and solutions that are rigorously evaluated and well-presented. Submissions that describe minor variations of existing methods or only make small or questionable improvements to existing algorithms are discouraged.

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Important dates:
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***Note the earlier submission deadlines***
Abstract submission: February 2, 2009
Paper submission: February 6, 2009
Notification: April 10, 2009
Conference dates: June 28 - July 1, 2009

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Areas of interest include, but are not limited to:
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Novel data mining algorithms
Data mining foundations
Innovative applications of data mining
Data mining and KDD systems and frameworks Mining data streams and sensor data Mining multi-media data Mining social networks and graph data Mining spatial and temporal data Mining biological and biomedical data Mining text, Web, semantic web and semi-structured data Mining dynamic data Pre-processing and post-processing in data mining Robust and scalable statistical methods Security, privacy, and adversarial data mining High performance and parallel/distributed data mining Mining tera-/peta-scale data Visual data mining and data visualization Data integration issues in mining Data and knowledge provenance in KDD

All submitted papers will be judged based on their technical merit, rigor, significance, originality, repeatability, relevance, and clarity. Papers submitted to KDD'09 should be original work, not previously published in a peer-reviewed conference or journal. Substantially similar versions of the paper submitted to KDD'09 should not be under review in another peer-reviewed conference or journal during the KDD-09 reviewing period.

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Repeatability guideline:
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Repeatability is a cornerstone of any scientific endeavor. To ensure the long term viability of the research output of the SIGKDD community, we require open-source/public distribution of the code and the datasets. In those cases where this is not possible due to proprietary considerations, every effort should be made to provide the binary executable. If proprietary datasets are used, every effort should also be made to apply the approach to similar publicly available datasets. Furthermore, the description of experimental results in submitted papers should be accompanied by all relevant implementation details and exact parameter specifications.

Peter Flach and Mohammed J. Zaki
KDD'09 Program Co-Chairs

John Elder and Francoise Soulie Fogelman General Chair