File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Hierarchical constraint satisfaction in spatial databases

TitleHierarchical constraint satisfaction in spatial databases
Authors
Issue Date1999
Citation
Proceedings Of The National Conference On Artificial Intelligence, 1999, p. 142-147 How to Cite?
AbstractSeveral 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.
Persistent Identifierhttp://hdl.handle.net/10722/152270

 

DC FieldValueLanguage
dc.contributor.authorPapadias, Dimitrisen_US
dc.contributor.authorKalnis, Panosen_US
dc.contributor.authorMamoulis, Nikosen_US
dc.date.accessioned2012-06-26T06:36:51Z-
dc.date.available2012-06-26T06:36:51Z-
dc.date.issued1999en_US
dc.identifier.citationProceedings Of The National Conference On Artificial Intelligence, 1999, p. 142-147en_US
dc.identifier.urihttp://hdl.handle.net/10722/152270-
dc.description.abstractSeveral 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.en_US
dc.languageengen_US
dc.relation.ispartofProceedings of the National Conference on Artificial Intelligenceen_US
dc.titleHierarchical constraint satisfaction in spatial databasesen_US
dc.typeArticleen_US
dc.identifier.emailMamoulis, Nikos:nikos@cs.hku.hken_US
dc.identifier.authorityMamoulis, Nikos=rp00155en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-0032596639en_US
dc.identifier.spage142en_US
dc.identifier.epage147en_US
dc.identifier.scopusauthoridPapadias, Dimitris=7005757795en_US
dc.identifier.scopusauthoridKalnis, Panos=6603477534en_US
dc.identifier.scopusauthoridMamoulis, Nikos=6701782749en_US

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats