Titlebook: Data Mining for Scientific and Engineering Applications; Robert L. Grossman,Chandrika Kamath,Raju R. Nambur Book 2001 Springer Science+Bus

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Searching for Bent-Double Galaxies in the First Survey,challenges we face in the application of data mining to a scientific data set. We explain why, in contrast with most commercial data mining applications, data preprocessing requires a considerable effort in scientific applications. Using decision tree classifiers, we describe the work we are doing i

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,EVITA — Efficient Visualization and Interrogation of Tera-Scale Data,o much of the work in the traditional data-mining community. We first describe the basic system and follow with a discussion of ongoing work, focusing on efforts in multiscale feature detection and progressive access. Finally, we demonstrate the system for a two-dimensional vector field derived from

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Parallel Algorithms for Clustering High-Dimensional Large-Scale Datasets,to an enormous amount of computation. We have introduced an adaptive grid framework which not only reduces the computation vastly by forming grids based on the data distribution, but also improves the quality of clustering. Clustering algorithms also need to explore clusters in a subspace of the tot

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Data Mining for Scientific and Engineering Applications978-1-4615-1733-7Series ISSN 1569-2698 Series E-ISSN 2468-8738

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Rocío A. Aúz García,Tobias Lotter We briefly describe some of the problems astronomical data and datasets present and give an example from our own efforts to auto- mate the classification of galaxies, and then discuss where “clustering” algorithms may be applicable.

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Cyberpunk und Open-Source-Religion bioinformatics and the motivating data management and analysis tasks. Descriptions of successful applications are given, along with an outline of the near-future potential and issues affecting the successful application of data mining.

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Keep Out, or Else: Diary as Body in , and leation-propagation model of protein folding. We apply a hybrid approach, using a Hidden Markov Model to extract folding initiation sites, and then apply association mining to discover contact potentials. The new hybrid approach achieves accuracy results better than those reported previously.