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Article: Ranking spatial data by quality preferences
Title | Ranking spatial data by quality preferences | ||||
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Authors | |||||
Keywords | Query processing spatial databases | ||||
Issue Date | 2011 | ||||
Publisher | I E E E. The Journal's web site is located at http://www.computer.org/tkde | ||||
Citation | Ieee Transactions On Knowledge And Data Engineering, 2011, v. 23 n. 3, p. 433-446 How to Cite? | ||||
Abstract | A spatial preference query ranks objects based on the qualities of features in their spatial neighborhood. For example, using a real estate agency database of 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 their spatial neighborhood. Such a neighborhood concept can be specified by the user via different functions. It can be an explicit circular region within a given distance from the flat. Another intuitive definition is to assign higher weights to the features based on their proximity to the flat. In this paper, we formally define spatial preference queries and propose appropriate indexing techniques and search algorithms for them. Extensive evaluation of our methods on both real and synthetic data reveals that an optimized branch-and-bound solution is efficient and robust with respect to different parameters. © 2006 IEEE. | ||||
Persistent Identifier | http://hdl.handle.net/10722/138038 | ||||
ISSN | 2023 Impact Factor: 8.9 2023 SCImago Journal Rankings: 2.867 | ||||
ISI Accession Number ID |
Funding Information: This work was supported by grant HKU 715509E from Hong Kong RGC. | ||||
References | |||||
Grants |
DC Field | Value | Language |
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dc.contributor.author | Yiu, ML | en_HK |
dc.contributor.author | Lu, H | en_HK |
dc.contributor.author | Mamoulis, N | en_HK |
dc.contributor.author | Vaitis, M | en_HK |
dc.date.accessioned | 2011-08-26T14:39:03Z | - |
dc.date.available | 2011-08-26T14:39:03Z | - |
dc.date.issued | 2011 | en_HK |
dc.identifier.citation | Ieee Transactions On Knowledge And Data Engineering, 2011, v. 23 n. 3, p. 433-446 | en_HK |
dc.identifier.issn | 1041-4347 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/138038 | - |
dc.description.abstract | A spatial preference query ranks objects based on the qualities of features in their spatial neighborhood. For example, using a real estate agency database of 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 their spatial neighborhood. Such a neighborhood concept can be specified by the user via different functions. It can be an explicit circular region within a given distance from the flat. Another intuitive definition is to assign higher weights to the features based on their proximity to the flat. In this paper, we formally define spatial preference queries and propose appropriate indexing techniques and search algorithms for them. Extensive evaluation of our methods on both real and synthetic data reveals that an optimized branch-and-bound solution is efficient and robust with respect to different parameters. © 2006 IEEE. | en_HK |
dc.language | eng | en_US |
dc.publisher | I E E E. The Journal's web site is located at http://www.computer.org/tkde | en_HK |
dc.relation.ispartof | IEEE Transactions on Knowledge and Data Engineering | en_HK |
dc.rights | ©2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | - |
dc.subject | Query processing | en_HK |
dc.subject | spatial databases | en_HK |
dc.title | Ranking spatial data by quality preferences | en_HK |
dc.type | Article | en_HK |
dc.identifier.email | Mamoulis, N:nikos@cs.hku.hk | en_HK |
dc.identifier.authority | Mamoulis, N=rp00155 | en_HK |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1109/TKDE.2010.119 | en_HK |
dc.identifier.scopus | eid_2-s2.0-79251513599 | en_HK |
dc.identifier.hkuros | 190926 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-79251513599&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 23 | en_HK |
dc.identifier.issue | 3 | en_HK |
dc.identifier.spage | 433 | en_HK |
dc.identifier.epage | 446 | en_HK |
dc.identifier.isi | WOS:000286207900009 | - |
dc.publisher.place | United States | en_HK |
dc.relation.project | Algorithms for Large-Scale Matching Problems | - |
dc.identifier.scopusauthorid | Yiu, ML=8589889600 | en_HK |
dc.identifier.scopusauthorid | Lu, H=26642953300 | en_HK |
dc.identifier.scopusauthorid | Mamoulis, N=6701782749 | en_HK |
dc.identifier.scopusauthorid | Vaitis, M=16240387400 | en_HK |
dc.identifier.issnl | 1041-4347 | - |