Download Advances in Database Technology - EDBT 2006: 10th by Martin Kersten (auth.), Yannis Ioannidis, Marc H. Scholl, PDF

By Martin Kersten (auth.), Yannis Ioannidis, Marc H. Scholl, Joachim W. Schmidt, Florian Matthes, Mike Hatzopoulos, Klemens Boehm, Alfons Kemper, Torsten Grust, Christian Boehm (eds.)

The sequence of foreign meetings on Extending Database know-how (EDBT) is a longtime and prestigious discussion board for the trade of the newest study leads to information administration. It presents exact possibilities for database researchers, practitioners, builders, and clients to discover new principles, thoughts, and instruments, and to switch stories. This quantity includes the court cases of the tenth EDBT convention, held in Munich, Germany, March 27-29, 2006. The convention integrated three keynote talks, fifty six sizeable and four half-size examine papers in 20 periods, eight commercial shows in three classes, 1 panel consultation, five tutorials in 7 periods, and 20 demonstrations in four periods. the entire study papers in addition to papers and abstracts from many of the different classes are integrated right here. exceptional individuals of the database and information-retrieval groups added the 3 keynotes, which have been all within the spirit of the banner subject selected for EDBT 2006: “From Database platforms to common info administration. ” Martin Kersten, a pioneer within the zone of database aid for ambient program environments and the investigator of numerous kernel database architectures, mentioned numerous difficult concerns that come up in natural database platforms, i. e. , structures that may be embedded in numerous functions and feature autonomic habit. Alan Smeaton, a pacesetter in content-based retrieval of knowledge in a wide selection of media, brought us to the realm of electronic video libraries and challenged us with a number of open difficulties linked to their powerful management.

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Additional resources for Advances in Database Technology - EDBT 2006: 10th International Conference on Extending Database Technology, Munich, Germany, March 26-31, 2006

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In Fig. 4 we illustrate on a stream that measures web usage, a comparison of our intelligent sampling method against the equi-sampling technique, which samples data at a specified time interval. We execute our algorithm for a specific threshold and reduce the data points within a window from M down to N 3 Note that the squared approximation error due to this sub-sampling scheme cannot be bounded in general for all signals, however we select it for its computational simplicity. In particular, for the wide variety of signals we consider in our experiments, we do not observe squared error significantly larger than the absolute squared threshold value.

Gilbert, S. Guha, P. Indyk, S. Muthukrishnan, and M. Strauss. Near-optimal Sparse Fourier Representations via Sampling. In STOC, pages 152–161, 2002. 9. M. Kontaki and A. Papadopoulos. Efficient similarity search in streaming time sequences. In SSDBM, 2004. 10. M. Lazarescu, S. Venkatesh, and H. H. Bui. Using Multiple Windows to Track Concept Drift. In Intelligent Data Analysis Journal, Vol 8(1), 2004. 11. S. Papadimitriou, A. Brockwell, and C. Faloutsos. Awsom: Adaptive, hands-off stream mining. In VLDB, pages 560–571, 2003.

S. Muthukrishnan. Data streams: algorithms and applications. In SODA, 2003. 21. R. Schmidt and C. Shahabi. “Propolyne: A fast wavelet-based technique for progressive evaluation of polynomial range-sum queries”. In EDBT, 2002. 22. E. J. Stollnitz, T. D. Derose, and D. H. Salesin. “Wavelets for computer graphics: theory and applications”. Morgan Kaufmann Publishers, 1996. 23. N. Thaper, S. Guha, P. Indyk, and N. Koudas. “Dynamic multidimensional histograms”. In ACM SIGMOD, 2002. 24. S. Vitter and M.

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