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Conference Paper: Top-k spatial preference queries

TitleTop-k spatial preference queries
Authors
Issue Date2007
Citation
Proceedings - International Conference On Data Engineering, 2007, p. 1076-1085 How to Cite?
AbstractA spatial preference query ranks objects based on the qualities of features in their spatial neighborhood. For example, consider a real estate agency office that holds a database with available flats for lease. A customer may want to rank the flats with respect to the appropriateness of their location, defined after aggregating the qualities of other features (e.g., restaurants, cafes, hospital, market, etc.) within a distance range from them. In this paper, we formally define spatial preference queries and propose appropriate indexing techniques and search algorithms for them. Our methods are experimentally evaluated for a wide range of problem settings. © 2007 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/93248
ISSN
2023 SCImago Journal Rankings: 1.306
References

 

DC FieldValueLanguage
dc.contributor.authorYiu, MLen_HK
dc.contributor.authorDai, Xen_HK
dc.contributor.authorMamoulis, Nen_HK
dc.contributor.authorVaitis, Men_HK
dc.date.accessioned2010-09-25T14:55:22Z-
dc.date.available2010-09-25T14:55:22Z-
dc.date.issued2007en_HK
dc.identifier.citationProceedings - International Conference On Data Engineering, 2007, p. 1076-1085en_HK
dc.identifier.issn1084-4627en_HK
dc.identifier.urihttp://hdl.handle.net/10722/93248-
dc.description.abstractA spatial preference query ranks objects based on the qualities of features in their spatial neighborhood. For example, consider a real estate agency office that holds a database with available flats for lease. A customer may want to rank the flats with respect to the appropriateness of their location, defined after aggregating the qualities of other features (e.g., restaurants, cafes, hospital, market, etc.) within a distance range from them. In this paper, we formally define spatial preference queries and propose appropriate indexing techniques and search algorithms for them. Our methods are experimentally evaluated for a wide range of problem settings. © 2007 IEEE.en_HK
dc.languageengen_HK
dc.relation.ispartofProceedings - International Conference on Data Engineeringen_HK
dc.titleTop-k spatial preference queriesen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailMamoulis, N:nikos@cs.hku.hken_HK
dc.identifier.authorityMamoulis, N=rp00155en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ICDE.2007.368966en_HK
dc.identifier.scopuseid_2-s2.0-34548771719en_HK
dc.identifier.hkuros137788en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-34548771719&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage1076en_HK
dc.identifier.epage1085en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridYiu, ML=8589889600en_HK
dc.identifier.scopusauthoridDai, X=8889338400en_HK
dc.identifier.scopusauthoridMamoulis, N=6701782749en_HK
dc.identifier.scopusauthoridVaitis, M=16240387400en_HK
dc.identifier.issnl1084-4627-

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