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 most recent learn leads to facts administration. It offers certain possibilities for database researchers, practitioners, builders, and clients to discover new principles, options, and instruments, and to replace stories. This quantity comprises the court cases of the tenth EDBT convention, held in Munich, Germany, March 27-29, 2006. The convention integrated three keynote talks, fifty six considerable and four half-size study papers in 20 periods, eight business shows in three periods, 1 panel consultation, five tutorials in 7 periods, and 20 demonstrations in four classes. the entire learn papers in addition to papers and abstracts from lots of the different classes are integrated the following. wonderful individuals of the database and information-retrieval groups brought the 3 keynotes, which have been all within the spirit of the banner subject selected for EDBT 2006: “From Database structures to common info administration. ” Martin Kersten, a pioneer within the zone of database help for ambient program environments and the investigator of numerous kernel database architectures, mentioned quite a few difficult concerns that come up in natural database platforms, i. e. , platforms that may be embedded in different functions and feature autonomic habit. Alan Smeaton, a pacesetter in content-based retrieval of data 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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Extra info for Advances in Database Technology - EDBT 2006: 10th International Conference on Extending Database Technology, Munich, Germany, March 26-31, 2006
Muthukrishnan. “What’s hot and what’s not: Tracking most frequent items dynamically”. In ACM PODS, 2003. 7. G. Cormode and S. Muthukrishnan. “What’s new: Finding significant differences in network data streams”. In IEEE Infocom, 2004. 8. A. Deligiannakis and N. Roussopoulos. “Extended wavelets for multiple measures”. In ACM SIGMOD, 2003. 9. A. Dobra, M. N. Garofalakis, J. Gehrke, and R. Rastogi. “Processing complex aggregate queries over data streams”. In ACM SIGMOD, 2002. 10. M. Garofalakis and A.
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Aref, and A. K. Elmagarmid. Using Convolution to Mine Obscure Periodic Patterns in One Pass. In EDBT, 2004. 6. F. Erg¨ un, S. Muthukrishnan, and S. C. Sahinalp. Sublinear methods for detecting periodic trends in data streams. In LATIN, 2004. 40 M. S. S. Yu 7. W. Fan. StreamMiner: A Classiﬁer Ensemble-based Engine to Mine Conceptdrifting Data Streams. In Proc. of VLDB, pages 1257–1260, 2004. 8. A. C. Gilbert, S. Guha, P. Indyk, S. Muthukrishnan, and M. Strauss. Near-optimal Sparse Fourier Representations via Sampling.
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.)