Advances in Spatial and Temporal Databases: 9th by Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Petra

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

It is our nice excitement to introduce the papers of the complaints of the ninth - ternational Symposium on Spatial and Temporal Databases – SSTD 2005. This year’s symposium keeps the culture of being the most popular discussion board for the presentation of study effects and event stories on innovative problems with spatialandtemporaldatabasesystems, together with facts models,systems,appli- tions and idea. The challenge of the symposium is to percentage leading edge recommendations that ful?ll the wishes of novel purposes and heterogeneous environments and determine new instructions for destiny learn and improvement. SSTD 2005 supplies researchers and practitioners a special chance to percentage their views with others attracted to many of the elements of database platforms for dealing with spatial and temporal information and for assisting their functions. a complete of seventy seven papers have been submitted this 12 months from numerous international locations. After an intensive assessment method, this system committee approved 24 papers protecting quite a few themes, together with indexing suggestions and question processing, cellular environments and relocating gadgets, and spatial and temporal information streams. we're more than happy with the range of the symposium’s subject matters, and we're pleased with the ensuing robust program.

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

Sample text

The six gray boxes, namely, apriori knowledge, selection, crossover, mutation, evaluation and refinement, and decoding, are the configurable components in GAMMA. They exhibit generality and flexibility for this framework. 1 An event is an activity which the object performs to change its moving behavior. The inverse operation is called decoding, which involves interpolating the locations at a time when no events occur. 1 In the sequel, unless otherwise stated, chromosome and trajectory are used interchangeably.

In ACM-GIS ’03: Proceedings of the 11th ACM International Symposium on Advances in Geographic Information Systems, pages 110–117, Nov 2003. 35. M. F. Mokbel, X. Xiong, W. G. Aref, S. Hambrusch, S. Prabhakar, and M. Hammad. PLACE: A Query Processor for Handling Real-time Spatio-temporal Data Streams (Demo). In VLDB ’04: Proceedings of the Thirtieth International Conference on Very Large Data Bases, Aug 2004. 36. M. Muralikrishna and D. J. DeWitt. Equi-depth Multidimensional Histograms. In SIGMOD ’88: Proceedings of the 1988 ACM SIGMOD international conference on Management of data, pages 28–36.

Not only the density of the moving objects change with time, but also there is some kind of periodicity in their behavior (as time repeats itself). For example, many people travel on weekends, yielding more traffic on the highways on Friday and Sunday evenings than on other week-evenings. Also, lots of traffic and congestion occur during the rush hour everyday. By detecting such patterns in the distribution of the moving objects, we believe that we can enhance the selectivity estimation. We illustrate the importance of having an ST-Histogram by the following example.

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