Advances in Spatial and Temporal Databases: 9th - download pdf or read online

By Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Petra Linhart (auth.), Claudia Bauzer Medeiros, Max J. Egenhofer, Elisa Bertino (eds.)

ISBN-10: 3540281274

ISBN-13: 9783540281276

It is our nice excitement to introduce the papers of the lawsuits of the ninth - ternational Symposium on Spatial and Temporal Databases – SSTD 2005. This year’s symposium maintains the culture of being the most desirable discussion board for the presentation of analysis effects and adventure stories on innovative problems with spatialandtemporaldatabasesystems, together with facts models,systems,appli- tions and conception. The project of the symposium is to percentage leading edge ideas that ful?ll the desires of novel functions and heterogeneous environments and determine new instructions for destiny learn and improvement. SSTD 2005 supplies researchers and practitioners a different chance to percentage their views with others drawn to some of the features of database structures for handling spatial and temporal information and for assisting their functions. a complete of seventy seven papers have been submitted this 12 months from a number of international locations. After a radical evaluation technique, this system committee authorized 24 papers protecting a number of subject matters, together with indexing strategies and question processing, cellular environments and relocating gadgets, and spatial and temporal information streams. we're more than happy with the diversity of the symposium’s subject matters, and we're happy with the ensuing powerful program.

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Read or Download Advances in Spatial and Temporal Databases: 9th International Symposium, SSTD 2005, Angra dos Reis, Brazil, August 22-24, 2005. Proceedings PDF

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Additional resources for Advances in Spatial and Temporal Databases: 9th International Symposium, SSTD 2005, Angra dos Reis, Brazil, August 22-24, 2005. Proceedings

Sample text

J. -W. Chung. Selectivity Estimation for Spatio-temporal Queries to Moving Objects. In SIGMOD ’02: Proceedings of the 2002 ACM SIGMOD international conference on Management of data, pages 440–451. ACM Press, 2002. 13. M. G. Elfeky, W. G. Aref, and A. K. Elmagarmid. Incremental, Online, and Merge Mining of Partial Periodic Patterns in Time-Series Databases. IEEE Transactions on Knowledge and Data Engineering (TKDE), 16(3):332–342, 2004. 14. C. Faloutsos, B. Seeger, A. Traina, and J. Caetano Traina.

The INSIDE query operator is proposed in [33] to check whether or not a moving object is in a certain range. Initially, at time t1 , the query optimizer finds that the selectivity of the INSIDE operator is less than the selectivity of the WHERE clause (Figure 2(a)). Thus the query optimizer picks up the query execution plan in Figure 2(b) to be used to answer the query. At time t2 , many vehicles enter the area A and this increases the selectivity of the INSIDE operator, and meanwhile the number of trucks decreases (Figure 2(c)).

A, b, c), then the time series can be considered a sequence over a finite alphabet Σ = {a, b, c, · · · }. Periodically, the histogram manager tries to see if any periodic pattern exists in any cell of the histogram. We use the periodicity mining technique in [13]. When we detect a periodic pattern in a dark cell of the grid, we no longer compute its selectivity estimate as being uniformly distributed on all the dark regions. Indeed, we call such cell “a shaded cell”. Shaded cells are treated as if there is a query that covers the whole cell.

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Advances in Spatial and Temporal Databases: 9th International Symposium, SSTD 2005, Angra dos Reis, Brazil, August 22-24, 2005. Proceedings by Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Petra Linhart (auth.), Claudia Bauzer Medeiros, Max J. Egenhofer, Elisa Bertino (eds.)


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