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Call for Papers Workshop on Knowledge Discovery, Modeling, and Simulation (KDMS-2011)

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  • William Rand
    ... Begin forwarded message: ************** Call for Papers Workshop on Knowledge Discovery, Modeling, and Simulation (KDMS-2011)
    Message 1 of 1 , May 31, 2011
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      Begin forwarded message:


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      Call for Papers
      Workshop on Knowledge Discovery, Modeling, and Simulation (KDMS-2011)
      San Diego, CA, August 21, 2011
      (co-located with SIG-KDD 2011)
       
      This first Workshop on Knowledge Discovery, Modeling and Simulation will be held in conjunction with the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining that will take place on August 21-24, 2011 in San Diego, CA.
       
      Knowledge discovery (KD) uncovers patterns and relationships within data. These patterns and relationships can, in turn, be used to create models of data. Simulations based on these models then can be used to generate data and start the cycle anew. Modeling and simulation (M&S) can benefit from KD by providing a means to evaluate the realism, novelty, interestingness, and utility of the created model. KD can benefit M&S by providing a means to understand the large amount of data generated by simulations. Recent developments in the ability to mine complex, highly-structured data of the form typically produced by large scale simulations may provide opportunities for useful knowledge discovery of simulation outputs.
       
      The organizers of this workshop believe that combining KD and M&S will be useful in a variety of application domains, including social sciences, economics, earth sciences, and life sciences. Moreover, there are a number of sub-disciplines of machine learning and data mining that lie at the confluence of KD with M&S, including graphical models, statistical relational learning, evolutionary computation and clustering.
       
      For example, models and simulations of financial transactions depend on accurate representation of social data, and the discovery of new patterns among these data. With the extremely large data volumes in the health care and energy domains, models and simulations intended to support resource planning rely on effective and rapid clustering techniques to learn usage patterns, as well as the early detection of patterns not previously represented in the model or simulation. And for those with a more physics-based modeling perspective, KD developments in time point-based and interval-based methods, as well as univariate and multivariate methods, are potentially applicable to complex climate models when combined with methods of spatial outlier detection.
       
      The goal of this workshop is to bring together researchers from a variety of these disciplines to define a research agenda for the convergence of two previously separate research areas: KD and M&S. Specific objectives are to identify:
       
      -- How knowledge discovery can produce patterns that can be useful in the development of models; 
      -- How to effectively and usefully mine the results of large numbers of potentially complex simulations created by executing models; and 
      -- Other potential synergies that may result from “closing the loop” between KD and M&S.
       
      As this is the first workshop of its nature in the KDD conference community, we hope participants will walk away with a better sense of the collaboration possible across these disciplines and a better appreciation of the tools available for combining KD and M&S techniques. Since our challenge is to identify the application of KD techniques and tools to real world applications, we call for papers in a variety of M&S domains, including:
       
      -- Social science, e.g., business interactions, cultural dynamics, crisis management 
      -- Earth science, e.g., meteorology, astronomy 
      -- Life science, e.g., medical diagnosis, pharma, biology, pandemic modeling 
      -- Infrastructure/logistics, e.g., emergency management, production scheduling, traffic flow 
      -- Massive online gaming, e.g., massive virtual reality training and exercise environments 
      -- Engineering, e.g., aircraft development, building design, energy efficiency 
      -- Cyber security, e.g., agent-based, large-scale simulation of networks 
      -- Business processes, e.g., strategic planning, resource allocation, portfolio management, marketing
       
      We invite researchers working at the confluence of KD and M&S to submit regular or position papers describing the major points and/or results they would present during a talk or discuss in a panel session. --Regular papers are a maximum of 8 pages long in two-column format, position papers comprise 2 pages. All authors should use the ACM KDD conference paper format with these lengths, to include all graphics and references.
       
      NEW: Papers should be submitted by June 8, 2011.
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