Conference Proceeding Article
Research on spatial network databases has so far considered that there is a single cost value associated with each road segment of the network. In most real-world situations, however, there may exist multiple cost types involved in transportation decision making. For example, the different costs of a road segment could be its Euclidean length, the driving time, the walking time, possible toll fee, etc. The relative significance of these cost types may vary from user to user. In this paper we consider such multi-cost transportation networks (MCN), where each edge (road segment) is associated with multiple cost values. We formulate skyline and top-k queries in MCNs and design algorithms for their efficient processing. Our solutions have two important properties in preference-based querying; the skyline methods are progressive and the top-k ones are incremental. The performance of our techniques is evaluated with experiments on a real road network.
Cost values, Euclidean, Preference queries, Preference-based, Real road networks, Real world situations, Road segments, Spatial network database, Top-k query, Transportation decision making, Transportation network
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
ICDE 2010: IEEE 26th International Conference on Data Engineering: Proceedings, Long Beach, California, USA, 1 - 6 March 2010
IEEE Computer Society
City or Country
Los Alamitos, CA
MOURATIDIS, Kyriakos; LIN, Yimin; and YIU, Man Lung.
Preference Queries in Large Multi-Cost Transportation Networks. (2010). ICDE 2010: IEEE 26th International Conference on Data Engineering: Proceedings, Long Beach, California, USA, 1 - 6 March 2010. 533-544. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/506
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