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Ranking Spatial Data by Quality Preferences
March 2011 (vol. 23 no. 3)
pp. 433-446
ASCII Text
x 
 
Man Lung Yiu, Hua Lu, Nikos Mamoulis, Michail Vaitis, "Ranking Spatial Data by Quality Preferences," IEEE Transactions on Knowledge and Data Engineering, vol. 23, no. 3, pp. 433-446, March, 2011.
 
 
BibTex
x
 
@article{ 10.1109/TKDE.2010.119,
author = {Man Lung Yiu and Hua Lu and Nikos Mamoulis and Michail Vaitis},
title = {Ranking Spatial Data by Quality Preferences},
journal ={IEEE Transactions on Knowledge and Data Engineering},
volume = {23},
number = {3},
issn = {1041-4347},
year = {2011},
pages = {433-446},
doi = {http://doi.ieeecomputersociety.org/10.1109/TKDE.2010.119},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Knowledge and Data Engineering
TI - Ranking Spatial Data by Quality Preferences
IS - 3
SN - 1041-4347
SP433
EP446
EPD - 433-446
A1 - Man Lung Yiu,
A1 - Hua Lu,
A1 - Nikos Mamoulis,
A1 - Michail Vaitis,
PY - 2011
KW - Query processing
KW - spatial databases.
VL - 23
JA - IEEE Transactions on Knowledge and Data Engineering
ER -
 
Man Lung Yiu, Hong Kong Politechnic University, Hong Kong
Hua Lu, Aalborg University, Aalborg
Nikos Mamoulis, University of Hong Kong, Hong Kong
Michail Vaitis, University of the Aegean, Mytilene
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.

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Index Terms:
Query processing, spatial databases.
Citation:
Man Lung Yiu, Hua Lu, Nikos Mamoulis, Michail Vaitis, "Ranking Spatial Data by Quality Preferences," IEEE Transactions on Knowledge and Data Engineering, vol. 23, no. 3, pp. 433-446, March 2011, doi:10.1109/TKDE.2010.119
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