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 overseas meetings on Extending Database expertise (EDBT) is a longtime and prestigious discussion board for the alternate of the newest learn ends up in facts administration. It offers particular possibilities for database researchers, practitioners, builders, and clients to discover new rules, innovations, and instruments, and to interchange studies. This quantity includes the complaints of the tenth EDBT convention, held in Munich, Germany, March 27-29, 2006. The convention incorporated three keynote talks, fifty six giant and four half-size examine papers in 20 classes, eight business displays in three classes, 1 panel consultation, five tutorials in 7 periods, and 20 demonstrations in four classes. all the examine papers in addition to papers and abstracts from many of the different periods are integrated the following. amazing contributors of the database and information-retrieval groups introduced the 3 keynotes, that have been all within the spirit of the banner topic 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 a number of tough concerns that come up in natural database platforms, i. e. , structures that may be embedded in different purposes and feature autonomic habit. Alan Smeaton, a pacesetter in content-based retrieval of knowledge in a large choice of media, brought us to the area of electronic video libraries and challenged us with numerous open difficulties linked to their potent management.
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Extra info for Advances in Database Technology - EDBT 2006: 10th International Conference on Extending Database Technology, Munich, Germany, March 26-31, 2006
Interest in data streams has also increased rapidly over the last years, as more algorithms are presented that provide solutions in a streaming one-pass, low memory environment. Overviews of data-streaming issues and algorithms can be found, for instance, in [3, 20]. Sketches first appeared for estimating the second frequency moment of a set of elements  and have since proven to be a useful summary structure in such a dynamic setting. Their application includes uses for estimating join sizes of queries over streams [1, 9], maintaining wavelet synopses , constructing histograms [12, 23], estimating frequent items [5, 6] and quantiles .
Wang. “Approximate computation of multidimensional aggregates of sparse data using wavelets”. In ACM SIGMOD, 1999. Resource Adaptive Periodicity Estimation of Streaming Data Michail Vlachos, Deepak S. Turaga, and Philip S. J. Watson Research Center, 19 Skyline Dr, Hawthorne, NY Abstract. Streaming environments typically dictate incomplete or approximate algorithm execution, in order to cope with sudden surges in the data rate. Such limitations are even more accentuated in mobile environments (such as sensor networks) where computational and memory resources are typically limited.
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. 12. A. Papoulis. Signal Analysis. McGraw-Hill, 1977. 13. W. H. Press, B. P. Flannery, S. A. Teukolsky, and W. T. Vetterling.
Advances in Database Technology - EDBT 2006: 10th International Conference on Extending Database Technology, Munich, Germany, March 26-31, 2006 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.)