Hierarchical constraint satisfaction in spatial databases

Dimitris Papadias*, Panos Kalnis, Nikos Mamoulis

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationProceedings of the National Conference on Artificial Intelligence
PublisherAAAI
Pages142-147
Number of pages6
ISBN (Print)0262511061
StatePublished - 1999
Externally publishedYes
EventProceedings of the 1999 16th National Conference on Artificial Intelligence (AAAI-99), 11th Innovative Applications of Artificial Intelligence Conference (IAAI-99) - Orlando, FL, USA
Duration: Jul 18 1999Jul 22 1999

Other

OtherProceedings of the 1999 16th National Conference on Artificial Intelligence (AAAI-99), 11th Innovative Applications of Artificial Intelligence Conference (IAAI-99)
CityOrlando, FL, USA
Period07/18/9907/22/99

ASJC Scopus subject areas

  • Software

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