Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/153

Hierarchical Constraint Satisfaction in Spatial Databases

Authors Papadias, Dimitris
Kalnis, Panos
Mamoulis, Nikos
Issue Date 1999
Source Proceedings of the National Conference on Artificial Intelligence , 1999, p. 142-147
Summary Several content-based queries in spatial databases and geographic information systems (GISs) can be modelled and processed as constraint satisfaction problems (CSPs). Regular CSP algorithms, however, work for main memory retrieval without utilizing indices to prune the search space. This paper shows how systematic and local search techniques can take advantage of the hierarchical decomposition of space, preserved by spatial data structures, to efficiently guide search. We study the conditions under which hierarchical constraint satisfaction outperforms traditional methods with extensive experimentation.
Note Proceedings of the 1999 16th National Conference on Artificial Intelligence (AAAI-99), 11th Innovative Applications of Artificial Intelligence Conference (IAAI-99); Orlando, FL, USA; ; 18 July 1999 through 22 July 1999; Code 55263
Subjects
ISBN 0262511061
Language English
Format Conference paper
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