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    KDD- 2009 - 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2009)

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    Website http://www.sigkdd.org/kdd2009/papers.html | Want to Edit it Edit Freely

    Category KDD- 2009

    Deadline: February 06, 2009 | Date: June 28, 2009

    Venue/Country: Paris, France

    Updated: 2010-06-04 19:32:22 (GMT+9)

    Call For Papers - CFP

    Important Dates

    Abstract Submission: February 2, 2009

    Electronic Paper Submission: February 6, 2009

    Notification: April 10, 2009

    Conference Dates: June 28 - July 1, 2009

    Please note the earlier submission date and the earlier conference date.

    Paper Submission

    Length of paper: NINE (9) pages in ACM template (Longer papers will be rejected without review)

    Format: PDF, US Letter (8.5" x 11").

    Templates: http://www.acm.org/sigs/publications/proceedings-templates

    Submission website: _TBD_

    The KDD-2009 review process will not be "double-blind"

    We cannot accept submissions by e-mail, fax or postal mail.

    Research Track Papers

    Call for Papers

    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.

    Areas of interest include, but are not limited to:

    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, sematic 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.

    Repeatability guideline: 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 Zaki, KDD'09 Program Co-Chairs

    Industrial/Government Applications Track

    Call for Papers

    Due Feb 6, 2009

    June 28 - July 1, 2009. Paris, France.

    The Industrial/Government Applications Track of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2009) will highlight challenges, lessons, and research issues arising out of deploying applications of KDD technology. The focus is on promoting the exchange of ideas between researchers and practitioners of data mining.

    The KDD-2009 Industrial/Government Applications (I/G) Track seeks to:

    provide a forum for exchanging ideas between KDD practitioners, researchers, companies, and government organizations

    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 implementations of KDD solutions relevant to commercial or government settings. The primary emphasis is on papers that advance our understanding of practical, applied, or pragmatic issues and highlight new research challenges in real KDD applications. Applications can be in any field including, but not limited to: e-commerce, medical and pharmaceutical, defense, public policy, engineering, manufacturing, telecommunications, and government. Being held in Europe for the first time, we enthusiastically seek contributions from European authors and on European projects.

    The I/G Applications Track will consist of competitively-selected contributed papers - presented in oral and/or poster form - as well as invited talks. We envision submissions along four sub-areas:

    Emerging applications and technology

    Deployed KDD case studies

    Comparative studies of KDD technology

    Pragmatic issues and research considerations in fielding real applications.

    Emerging application and technology 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 general impact of the work clearly. Comparative studies compare and contrast KDD technologies using specific examples (without 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.

    KDD 2009 will also feature keynote presentations, a research track, workshops, tutorials, and the KDD Cup competition.

    I/G Applications Track Co-Chairs

    Kamal Ali, ISLE/Stanford

    Ricardo Baeza-Yates, Yahoo! Research


    Keywords: Accepted papers list. Acceptance Rate. EI Compendex. Engineering Index. ISTP index. ISI index. Impact Factor.
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